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oBE&_L^K$Vqox1Ojhs@R)|o50+1L3ClDI}aUl?c_=|y<2;dkJ5(HHS(lG;wxzV&S oBE&_L^K$Vqox1Ojhs@R)|o50+1L3ClDI}aUl?c_=|y<2;dkJ5(HHS(lG;wxzV&S oBE&_L^K$Vqox1Ojhs@R)|o50+1L3ClDI}aUl?c_=|y<2;dkJ5(HHS(lG;wxzV&S oBE&_L^K$Vqox1Ojhs@R)|o50+1L3ClDI}aUl?c_=|y<2;dkJ5(HHS(lG;wxzV&S oBE&_L^K$Vqox1Ojhs@R)|o50+1L3ClDI}aUl?c_=|y<2;dkJ5(HHS(lG;wxzV&S oBE&_L^K$Vqox1Ojhs@R)|o50+1L3ClDI}aUl?c_=|y<2;dkJ5(HHS(lG;wxzV&S oBE&_L^K$Vqox1Ojhs@R)|o50+1L3ClDI}aUl?c_=|y<2;dkJ5(HHS(lG;wxzV&S oBE&_L^K slogans. +* **Be useful first, promotional second.** + +## Tone knobs (when to use which) + +* **Bold:** when you’re saying a truth users already feel (“Most vibe-coded apps die at auth + DB.”) +* **Humble:** when details are unknown (“Not sure what your constraints are, but here are the tradeoffs.”) +* **Ironic:** to puncture hype (“If your ‘AI platform’ can’t run tests, it’s a chatbot wearing a hard hat.”) +* **Serious:** for security, privacy, business-critical advice. + +## Hard don’ts + +* Don’t claim “instant” anything unless it’s literally instant. +* Don’t dunk on competitors personally. Critique **constraints**, not founders. +* Don’t reveal client confidentials or private business numbers. +* Don’t promise timelines/prices/features you can’t guarantee. +* Don’t argue forever. One correction, one explanation, exit. + +--- + +# 5) Twitter playbook + +## Format patterns that sound like me + +**Pattern A: Hot take + 3 bullets** + +* One punchy sentence. +* 3 bullets (max). +* Close with a question. + +**Pattern B: First principles** + +* “The real problem isn’t X. It’s Y.” +* 2–4 lines of reasoning. + +**Pattern C: “If/then” practical advice** + +* “If you only need __, use __.” +* “If you need __, you’ll want __.” + +## Example tweets (ready-to-use) + +1. + +Vibe-coding is fun until you add: auth, a database, and background jobs. +Then it’s not “vibes.” It’s software engineering again. + +2. + +Most “prompt-to-app” tools optimize for *first demo*. +The real test is change #5. +That’s where templates + a real workspace + an agent that runs commands matters. + +3. + +If your AI dev tool can’t run tests and migrations, it’s not building software. +It’s writing fan fiction in TypeScript. + +4. + +We’re building Appwizzy around a simple idea: +**machine + template + agent**. +Less magic. More repeatability. + +## CTA etiquette on Twitter + +* Don’t drop links in every reply. +* If asked “what tool?”, respond: + + * 80% value, 20% mention Appwizzy. + * “If you want, I can share the template we use.” + +--- + +# 6) Reddit playbook + +Reddit hates marketing and loves competence. + +## Reddit rules + +* Lead with the answer, then the reasoning. +* Be candid about tradeoffs. +* Use specifics (stacks, failure modes, constraints). +* Avoid “we built a platform…” unless asked. Instead: + + * “One approach that works: machine + template + agent…” + +## Example Reddit comment (ready-to-use) + +> Most vibe-coding tools are great at “first demo.” +> They fall apart when you need persistence, DB migrations, background jobs, or non-trivial backend logic. +> +> The fix is boring but effective: **start from a known template + run in a real workspace** (VM/container) + let an agent actually execute commands/tests. +> +> That gives you repeatability. And repeatability is what turns demos into products. + +## How to handle skepticism + +* Agree with the valid part. +* Separate hype from reality. +* Give a concrete test they can run. + +Example: + +> You’re right to be skeptical. Most “AI builders” are demo factories. +> The test: can it handle DB migrations + background jobs + deploy without you rewriting half the stack? +> If yes, it’s a tool. If no, it’s entertainment. + +--- + +# 7) Common reply scenarios (copy/paste templates) + +## “Why not just use Lovable/Bolt/v0?” + +* **Short:** + “They’re great for demos/UI. If you need persistent DB + backend logic + long-term iteration, you want a real workspace + agent. Different job.” +* **Longer:** + “I like those tools for prototypes. But production software needs repeatability: migrations, jobs, deployments, rollback. That’s why we’re building Appwizzy around templates + real environments.” + +## “What’s your unfair advantage?” + +* “We’re template-first + environment-first. + The agent isn’t just chatting — it’s executing inside a real workspace. + That’s the difference between a preview and a product.” + +## “Isn’t this just Replit?” + +* “Replit is closest. The difference is philosophy: we’re optimizing for ‘pro’ outcomes — templates, ownership/export, reproducibility, and long-term iteration — not just first-time wow.” + +## “How do I choose stack/template?” + +* “Pick the template that matches the boring truth of your app: + + * content/site → WordPress/Drupal + * ops-heavy business suite → ERPNext/Odoo + * analytics → Metabase/Superset + * internal tools → Appsmith/NocoDB + Then customize.” + +## Troll / hostile + +* One reply max: + “Fair. If you only need a quick demo, there are easier tools. We’re building for people who need to maintain the thing after the demo.” +* Then stop. + +--- + +# 8) The “philosophical” style (how to do it without being cringe) + +I sometimes drop first-principles lines. Do it like this: + +* Start with a concrete pain. +* Name the underlying truth. +* Provide a practical consequence. + +Example: + +> The hard part of software isn’t writing code. +> It’s keeping a system correct while it changes. +> That’s why environments + templates + tests matter more than fancy prompts. + +--- + +# 9) Final checklist for the EA (before hitting “post”) + +* Does this sound like a human who’s built things? +* Is it **useful** even if the reader never clicks our link? +* Did we avoid absolute promises (“instantly,” “guaranteed,” “always”)? +* Did we avoid unverifiable claims (big logos, secret clients)? +* Is the tone: confident, direct, slightly witty, not salesy? + +--- + +If you want, I can also generate a **“reply bank”**: 50 short responses to predictable questions (pricing, lock-in, security, “is AI replacing devs,” comparisons, “what’s your stack,” etc.) in *your* voice, ready for copy/paste. diff --git a/aiea/LOCAL_SCREENSHOT_EXTENSION.md b/aiea/LOCAL_SCREENSHOT_EXTENSION.md new file mode 100644 index 0000000..fe42fa8 --- /dev/null +++ b/aiea/LOCAL_SCREENSHOT_EXTENSION.md @@ -0,0 +1,59 @@ +# Local Chrome Screenshot Extension (Unpacked) + +This is a local-only setup (no publishing) that: + +1. Captures the visible tab as a PNG from a Chrome extension popup. +2. Sends it to a local HTTP server on `127.0.0.1`. +3. Extracts simplified page content (text + a pruned “content tree”) from the active tab. +4. The server saves it into `./screenshots/` and optionally runs a local script. + +## 1) Start the local server + +From the project root (recommended: use a venv): + +```bash +python3 -m venv .venv +source .venv/bin/activate +pip install -U pip +pip install -r requirements.txt + +export OPENAI_API_KEY="..." + +python3 tools/local_screenshot_bridge.py --port 8765 --out-dir screenshots --ai +``` + +Notes: + +- The server listens on `http://127.0.0.1:8765/screenshot`. +- If you omit `--ai`, it will only save files (no OpenAI call). +- If you set `--ai`, it will generate reply suggestions and return them back to the extension (and also save `*.ai.json`). +- If you're debugging, add `--log-level debug` (or set `AIEA_LOG_LEVEL=debug`) for more detail. +- Optional: you can still use `--run ...` as a post-save hook. + +## 2) Load the extension (unpacked) + +1. Open Chrome: `chrome://extensions` +2. Enable "Developer mode" +3. Click "Load unpacked" +4. Select: `chrome_screenshot_ext/` + +## 3) Use it + +1. Click the extension icon. +2. Confirm the endpoint is `http://127.0.0.1:8765/screenshot`. +3. Optionally add "Extra instructions" (saved locally in the extension). +4. Click "Capture". +5. Use the "History" dropdown + "Show" to view older AI suggestions. + +Saved files land in `screenshots/`: + +- `YYYYMMDDTHHMMSSZ-.png` +- `YYYYMMDDTHHMMSSZ-.json` +- `YYYYMMDDTHHMMSSZ-.content.json` +- `YYYYMMDDTHHMMSSZ-.ai.json` (when `OPENAI_API_KEY` is set) + +Alternatively create `.env` in the project root: + +```bash +OPENAI_API_KEY=... +``` diff --git a/aiea/README.md b/aiea/README.md new file mode 100644 index 0000000..fa56c23 --- /dev/null +++ b/aiea/README.md @@ -0,0 +1,157 @@ +# AIEA Local Chrome Screenshot + OpenAI Assistant + +Local-only (unpacked) Chrome extension + Python bridge that: + +1. Captures the visible tab screenshot. +2. Extracts visible page text hierarchy (reduced HTML tree). +3. Saves files to `./screenshots`. +4. Calls OpenAI with: + - screenshot image + - extracted page content + - system instructions from `AI_EA_INSTRUCTIONS.MD` + - optional extra instructions from the extension UI +5. Returns short + medium response suggestions per visible post back to the extension popup. + +No Chrome Web Store publishing is required. + +## Project Structure + +- `chrome_screenshot_ext/` unpacked MV3 extension (popup UI + capture + extraction) +- `tools/local_screenshot_bridge.py` local HTTP server (`127.0.0.1`) + OpenAI call +- `AI_EA_INSTRUCTIONS.MD` system instructions fed to the model +- `screenshots/` generated outputs (`.png`, `.json`, `.content.json`, `.ai.json`) + +## Prerequisites + +- macOS/Linux shell +- Python 3.9+ +- Google Chrome +- OpenAI API key + +## Setup (venv) + +From repo root: + +```bash +python3 -m venv .venv +source .venv/bin/activate +pip install -U pip +pip install -r requirements.txt +``` + +Set API key with either: + +1. Environment variable +```bash +export OPENAI_API_KEY="your_api_key_here" +``` + +2. `.env` file in project root +```bash +OPENAI_API_KEY=your_api_key_here +``` + +## Run the Local Server + +With OpenAI enabled: + +```bash +python3 tools/local_screenshot_bridge.py --port 8765 --out-dir screenshots --ai +``` + +Without OpenAI (save files only): + +```bash +python3 tools/local_screenshot_bridge.py --port 8765 --out-dir screenshots +``` + +More logging (includes AI request/response ids + parse details): + +```bash +python3 tools/local_screenshot_bridge.py --port 8765 --out-dir screenshots --ai --log-level debug + +python3 tools/local_screenshot_bridge.py --port 8765 --out-dir screenshots --ai --log-level debug --ai-max-output-tokens 2500 +``` + +Health check: + +```bash +curl http://127.0.0.1:8765/health +``` + +## Load the Chrome Extension (Unpacked) + +1. Open `chrome://extensions` +2. Enable Developer mode +3. Click `Load unpacked` +4. Select `chrome_screenshot_ext/` + +If you change extension code, click `Reload` on this extension page. + +## Use the Extension + +1. Open any normal webpage (not `chrome://` pages). +2. Click extension icon. +3. Keep endpoint: `http://127.0.0.1:8765/screenshot` +4. Optional: add `Extra instructions` (2-line input in popup). +5. Click `Capture`. + +Popup shows: + +- Saved file paths +- AI suggestions per detected post (6 total): + - improved short + medium + - critical short + medium + - suggested short + medium +- Any AI error details + +History in popup: + +- `History` dropdown stores recent generations locally (`chrome.storage.local`) +- `Show` displays a previous result +- `Clear` removes local popup history + +## Output Files + +Generated in `screenshots/`: + +- `YYYYMMDDTHHMMSSZ-.png` screenshot +- `YYYYMMDDTHHMMSSZ-.json` metadata +- `YYYYMMDDTHHMMSSZ-.content.json` extracted visible content tree +- `YYYYMMDDTHHMMSSZ-.ai.json` structured AI suggestions + +## AI Behavior Notes + +- System instructions source: `AI_EA_INSTRUCTIONS.MD` +- Extra per-capture instructions source: popup `Extra instructions` +- AI output is sanitized post-generation: + - quote/dash/space cleanup + - invisible unicode cleanup + - collapsed extra spaces/newlines + - forced lowercase (no capital letters) + +## Useful CLI Options + +```bash +python3 tools/local_screenshot_bridge.py --help +``` + +Common options: + +- `--ai-model` (default: `gpt-5.2`) +- `--ai-max-posts` (default: `12`) +- `--ai-content-max-chars` (default: `120000`) +- `--ai-image-detail` (default: `auto`) +- `--ai-max-output-tokens` (default: `1400`) +- `--run ...` optional post-save hook command + +## Troubleshooting + +- `missing_openai_api_key`: + set `OPENAI_API_KEY` in shell or `.env`, then restart server. +- `missing_openai_sdk`: + run `pip install -r requirements.txt` inside your venv. +- Capture fails on Chrome internal pages: + `chrome://*`, Web Store, and some protected tabs cannot be scripted. +- No AI results in popup: + verify server started with `--ai`. diff --git a/aiea/chrome_screenshot_ext/manifest.json b/aiea/chrome_screenshot_ext/manifest.json new file mode 100644 index 0000000..c9fe1be --- /dev/null +++ b/aiea/chrome_screenshot_ext/manifest.json @@ -0,0 +1,11 @@ +{ + "manifest_version": 3, + "name": "Local Screenshot Saver (Unpacked)", + "version": "0.1.0", + "description": "Capture the visible tab and send it to a local server that saves into this project and optionally runs a script.", + "action": { + "default_popup": "popup.html" + }, + "permissions": ["activeTab", "tabs", "storage", "scripting"], + "host_permissions": ["http://127.0.0.1/*", "http://localhost/*"] +} diff --git a/aiea/chrome_screenshot_ext/popup.html b/aiea/chrome_screenshot_ext/popup.html new file mode 100644 index 0000000..cb4cb50 --- /dev/null +++ b/aiea/chrome_screenshot_ext/popup.html @@ -0,0 +1,141 @@ + + + + + + Local Screenshot + + + +
+
Local Screenshot Saver
+ + + + +
+ + +
+ + +
+ + +
+ 

+    

+    
+  
+
diff --git a/aiea/chrome_screenshot_ext/popup.js b/aiea/chrome_screenshot_ext/popup.js
new file mode 100644
index 0000000..efb6512
--- /dev/null
+++ b/aiea/chrome_screenshot_ext/popup.js
@@ -0,0 +1,528 @@
+const DEFAULT_ENDPOINT = "http://127.0.0.1:8765/screenshot";
+const HISTORY_KEY = "capture_history_v1";
+const HISTORY_LIMIT = 25;
+const EXTRA_INSTRUCTIONS_KEY = "extra_instructions_v1";
+
+function $(id) {
+  return document.getElementById(id);
+}
+
+function setStatus(msg, kind) {
+  const el = $("status");
+  el.textContent = msg;
+  el.className = kind || "";
+}
+
+async function storageGet(key) {
+  return new Promise((resolve) => {
+    chrome.storage.local.get([key], (res) => resolve(res[key]));
+  });
+}
+
+async function storageSet(obj) {
+  return new Promise((resolve) => {
+    chrome.storage.local.set(obj, () => resolve());
+  });
+}
+
+function clampString(s, maxLen) {
+  const t = String(s || "");
+  if (t.length <= maxLen) return t;
+  return t.slice(0, Math.max(0, maxLen - 1)) + "…";
+}
+
+function renderResult(entryOrResp) {
+  const resp = entryOrResp && entryOrResp.png_path ? entryOrResp : entryOrResp && entryOrResp.resp ? entryOrResp.resp : entryOrResp;
+  const meta = entryOrResp && entryOrResp.title ? entryOrResp : null;
+
+  const lines = [];
+  lines.push("Saved:");
+  lines.push(`  PNG:  ${resp.png_path || "(unknown)"}`);
+  lines.push(`  META: ${resp.meta_path || "(unknown)"}`);
+  if (resp.content_path) lines.push(`  CONTENT: ${resp.content_path}`);
+  if (meta && meta.url) lines.push(`  URL:  ${meta.url}`);
+  if (meta && meta.extra_instructions) lines.push(`  EXTRA: ${clampString(meta.extra_instructions, 220)}`);
+
+  if (resp.ai_result) {
+    if (resp.ai_result.ok && resp.ai_result.ai && Array.isArray(resp.ai_result.ai.posts)) {
+      lines.push("");
+      {
+        const ms = resp.ai_result.took_ms || "?";
+        const model = resp.ai_result.model ? ` model=${resp.ai_result.model}` : "";
+        const rid = resp.ai_result.response_id ? ` id=${resp.ai_result.response_id}` : "";
+        const status = resp.ai_result.status && resp.ai_result.status !== "completed" ? ` status=${resp.ai_result.status}` : "";
+        const inc = resp.ai_result.incomplete_reason ? ` incomplete=${resp.ai_result.incomplete_reason}` : "";
+        lines.push(`AI (${ms}ms${model}${rid}${status}${inc}):`);
+      }
+      for (const p of resp.ai_result.ai.posts) {
+        const idx = typeof p.index === "number" ? p.index : "?";
+        const postText = (p.post_text || "").replace(/\s+/g, " ").trim();
+
+        // Back-compat with older saved results.
+        const hasNew =
+          "improved_short" in p ||
+          "improved_medium" in p ||
+          "critical_short" in p ||
+          "critical_medium" in p ||
+          "suggested_short" in p ||
+          "suggested_medium" in p;
+
+        const improvedShort = (p.improved_short || "").replace(/\s+/g, " ").trim();
+        const improvedMedium = (p.improved_medium || "").replace(/\s+/g, " ").trim();
+        const criticalShort = (p.critical_short || "").replace(/\s+/g, " ").trim();
+        const criticalMedium = (p.critical_medium || "").replace(/\s+/g, " ").trim();
+        const suggestedShort = (p.suggested_short || "").replace(/\s+/g, " ").trim();
+        const suggestedMedium = (p.suggested_medium || "").replace(/\s+/g, " ").trim();
+
+        const shortLegacy = (p.short_response || "").replace(/\s+/g, " ").trim();
+        const mediumLegacy = (p.medium_response || "").replace(/\s+/g, " ").trim();
+        lines.push("");
+        lines.push(`#${idx} Post: ${clampString(postText, 180)}`);
+        if (hasNew) {
+          lines.push(`  improved (short):   ${improvedShort}`);
+          lines.push(`  improved (medium):  ${improvedMedium}`);
+          lines.push(`  Critical (short): ${criticalShort}`);
+          lines.push(`  Critical (medium): ${criticalMedium}`);
+          lines.push(`  Suggested (short): ${suggestedShort}`);
+          lines.push(`  Suggested (medium): ${suggestedMedium}`);
+        } else {
+          lines.push(`  Short:  ${shortLegacy}`);
+          lines.push(`  Medium: ${mediumLegacy}`);
+        }
+      }
+      if (resp.ai_result.ai_path) lines.push(`\nAI file: ${resp.ai_result.ai_path}`);
+      if (resp.ai_result.usage && typeof resp.ai_result.usage === "object") {
+        const u = resp.ai_result.usage;
+        const ins = typeof u.input_tokens === "number" ? u.input_tokens : null;
+        const outs = typeof u.output_tokens === "number" ? u.output_tokens : null;
+        const tots = typeof u.total_tokens === "number" ? u.total_tokens : null;
+        const parts = [];
+        if (ins != null) parts.push(`in=${ins}`);
+        if (outs != null) parts.push(`out=${outs}`);
+        if (tots != null) parts.push(`total=${tots}`);
+        if (parts.length) lines.push(`AI usage: ${parts.join(" ")}`);
+      }
+    } else {
+      lines.push("");
+      const ms = resp.ai_result.took_ms || "?";
+      const model = resp.ai_result.model ? ` model=${resp.ai_result.model}` : "";
+      const rid = resp.ai_result.response_id ? ` id=${resp.ai_result.response_id}` : "";
+      const status = resp.ai_result.status ? ` status=${resp.ai_result.status}` : "";
+      const inc = resp.ai_result.incomplete_reason ? ` incomplete=${resp.ai_result.incomplete_reason}` : "";
+      const err = resp.ai_result.error || (resp.ai_result.ai && resp.ai_result.ai.error) || "unknown";
+      lines.push(`AI error (${ms}ms${model}${rid}${status}${inc}): ${err}`);
+      if (resp.ai_result.detail) lines.push(`Detail: ${clampString(resp.ai_result.detail, 600)}`);
+      if (resp.ai_result.raw_preview) lines.push(`Raw: ${clampString(resp.ai_result.raw_preview, 600)}`);
+      if (resp.ai_result.usage && typeof resp.ai_result.usage === "object") {
+        const u = resp.ai_result.usage;
+        const ins = typeof u.input_tokens === "number" ? u.input_tokens : null;
+        const outs = typeof u.output_tokens === "number" ? u.output_tokens : null;
+        const tots = typeof u.total_tokens === "number" ? u.total_tokens : null;
+        const parts = [];
+        if (ins != null) parts.push(`in=${ins}`);
+        if (outs != null) parts.push(`out=${outs}`);
+        if (tots != null) parts.push(`total=${tots}`);
+        if (parts.length) lines.push(`AI usage: ${parts.join(" ")}`);
+      }
+      if (resp.ai_result.ai_path) lines.push(`AI file: ${resp.ai_result.ai_path}`);
+    }
+  }
+
+  if (resp.ran) {
+    lines.push("Ran:");
+    if (resp.ran.error) {
+      lines.push(`  error: ${resp.ran.error}`);
+    } else {
+      lines.push(`  exit: ${resp.ran.exit_code}`);
+      if (resp.ran.stdout) lines.push(`  stdout: ${resp.ran.stdout.trim()}`);
+      if (resp.ran.stderr) lines.push(`  stderr: ${resp.ran.stderr.trim()}`);
+    }
+  }
+
+  return lines.join("\n");
+}
+
+async function loadHistory() {
+  const h = (await storageGet(HISTORY_KEY)) || [];
+  return Array.isArray(h) ? h : [];
+}
+
+async function saveHistory(history) {
+  await storageSet({ [HISTORY_KEY]: history });
+}
+
+function historyLabel(item) {
+  const when = item.saved_at ? item.saved_at.replace("T", " ").replace("Z", "Z") : "";
+  const t = item.title ? clampString(item.title, 36) : "";
+  const u = item.url ? clampString(item.url, 46) : "";
+  const base = t || u || item.id || "";
+  return when ? `${when} | ${base}` : base;
+}
+
+async function refreshHistoryUI() {
+  const sel = $("history");
+  const history = await loadHistory();
+  sel.textContent = "";
+
+  if (!history.length) {
+    const opt = document.createElement("option");
+    opt.value = "";
+    opt.textContent = "(empty)";
+    sel.appendChild(opt);
+    sel.disabled = true;
+    return;
+  }
+
+  sel.disabled = false;
+  for (const item of history) {
+    const opt = document.createElement("option");
+    opt.value = item.id || item.png_path || item.meta_path || "";
+    opt.textContent = historyLabel(item);
+    sel.appendChild(opt);
+  }
+}
+
+async function getActiveTab() {
+  const tabs = await chrome.tabs.query({ active: true, currentWindow: true });
+  return tabs[0] || null;
+}
+
+async function captureVisibleTab() {
+  // Defaults to current window when windowId is null.
+  return await chrome.tabs.captureVisibleTab(null, { format: "png" });
+}
+
+async function extractPageContent(tabId) {
+  const [{ result }] = await chrome.scripting.executeScript({
+    target: { tabId },
+    func: () => {
+      const SKIP_TAGS = new Set(["script", "style", "noscript", "template", "head", "meta", "link", "svg", "canvas"]);
+
+      const MAX_DEPTH = 14;
+      const MAX_NODES = 1800;
+      const MAX_TEXT_NODE_LEN = 500;
+
+      let nodeCount = 0;
+      let truncated = false;
+
+      function cleanText(s) {
+        return String(s || "")
+          .replace(/\s+/g, " ")
+          .trim();
+      }
+
+      function rectIntersectsViewport(r) {
+        const vw = window.innerWidth || document.documentElement.clientWidth || 0;
+        const vh = window.innerHeight || document.documentElement.clientHeight || 0;
+        return r.bottom > 0 && r.right > 0 && r.top < vh && r.left < vw;
+      }
+
+      function isVisibleElement(el) {
+        try {
+          const cs = window.getComputedStyle(el);
+          if (!cs) return false;
+          if (cs.display === "none" || cs.visibility === "hidden") return false;
+          const op = Number(cs.opacity || "1");
+          if (!Number.isNaN(op) && op <= 0.02) return false;
+          const r = el.getBoundingClientRect();
+          if ((r.width || 0) < 1 || (r.height || 0) < 1) return false;
+          if (!rectIntersectsViewport(r)) return false;
+          return true;
+        } catch {
+          return false;
+        }
+      }
+
+      function hasMeaningfulAttrs(el) {
+        const role = (el.getAttribute("role") || "").trim();
+        if (role) return true;
+        const aria = (el.getAttribute("aria-label") || "").trim();
+        if (aria) return true;
+        const dt = (el.getAttribute("data-testid") || "").trim();
+        if (dt) return true;
+        const tag = el.tagName.toLowerCase();
+        if (tag === "a" && (el.getAttribute("href") || el.href)) return true;
+        if (tag === "button" || tag === "input" || tag === "textarea" || tag === "select") return true;
+        return false;
+      }
+
+      function directVisibleText(el) {
+        // Only include immediate text nodes and form values. This avoids duplicating text up the tree.
+        const parts = [];
+
+        for (const n of Array.from(el.childNodes || [])) {
+          if (n.nodeType === Node.TEXT_NODE) {
+            const t = cleanText(n.nodeValue || "");
+            if (t) parts.push(t.length > MAX_TEXT_NODE_LEN ? t.slice(0, MAX_TEXT_NODE_LEN - 1) + "…" : t);
+          }
+        }
+
+        const tag = el.tagName.toLowerCase();
+        if (tag === "input") {
+          const type = (el.getAttribute("type") || "text").toLowerCase();
+          if (!["hidden", "submit", "button"].includes(type)) {
+            const v = cleanText(el.value || el.getAttribute("value") || el.getAttribute("placeholder") || "");
+            if (v) parts.push(v);
+          }
+        } else if (tag === "textarea") {
+          const v = cleanText(el.value || el.getAttribute("placeholder") || "");
+          if (v) parts.push(v);
+        }
+
+        return cleanText(parts.join(" "));
+      }
+
+      function simplifyTag(tag) {
+        // Keep some semantics; treat most wrapper tags as "div".
+        if (["main", "article", "section", "ul", "ol", "li", "p"].includes(tag)) return tag;
+        if (tag.match(/^h[1-6]$/)) return tag;
+        if (["a", "button", "label"].includes(tag)) return tag;
+        if (["header", "footer", "nav", "aside"].includes(tag)) return tag;
+        return "div";
+      }
+
+      function shouldSkip(el, tag) {
+        if (SKIP_TAGS.has(tag)) return true;
+        // Skip common overlay noise.
+        const id = (el.id || "").toLowerCase();
+        if (id.includes("cookie") || id.includes("consent")) return true;
+        return false;
+      }
+
+      function collapseWrappers(node) {
+        // Collapse div/span wrappers: div > div > div ... with a single child and no text/attrs.
+        // We only collapse when the wrapper has exactly one child.
+        while (
+          node &&
+          node.tag === "div" &&
+          !node.text &&
+          !node.attrs &&
+          Array.isArray(node.children) &&
+          node.children.length === 1 &&
+          node.children[0] &&
+          node.children[0].tag
+        ) {
+          node = node.children[0];
+        }
+        return node;
+      }
+
+      function maybeHoistInlineText(node) {
+        // Common pattern: Text or 
+        if (!node || node.text) return node;
+        if (!["a", "button", "label", "p", "li"].includes(node.tag)) return node;
+        if (!Array.isArray(node.children) || node.children.length !== 1) return node;
+        const ch = node.children[0];
+        if (ch && ch.text && (!ch.children || ch.children.length === 0) && (!ch.attrs || Object.keys(ch.attrs).length === 0)) {
+          node.text = ch.text;
+          delete node.children;
+        }
+        return node;
+      }
+
+      function build(el, depth) {
+        if (truncated) return null;
+        if (!el || depth > MAX_DEPTH) return null;
+        if (!(el instanceof Element)) return null;
+
+        const rawTag = el.tagName.toLowerCase();
+        if (shouldSkip(el, rawTag)) return null;
+        if (!isVisibleElement(el)) return null;
+
+        nodeCount += 1;
+        if (nodeCount > MAX_NODES) {
+          truncated = true;
+          return null;
+        }
+
+        const tag = simplifyTag(rawTag);
+        const text = directVisibleText(el);
+
+        const children = [];
+        for (const ch of Array.from(el.children || [])) {
+          const n = build(ch, depth + 1);
+          if (n) children.push(n);
+          if (truncated) break;
+        }
+
+        if (!text && children.length === 0) return null;
+
+        const node = { tag };
+        if (text) node.text = text;
+
+        // Only keep attrs when they help identify purpose/action.
+        if (hasMeaningfulAttrs(el)) {
+          const attrs = {};
+          const role = (el.getAttribute("role") || "").trim();
+          const aria = (el.getAttribute("aria-label") || "").trim();
+          const dt = (el.getAttribute("data-testid") || "").trim();
+          if (role) attrs.role = role;
+          if (aria) attrs.aria_label = aria;
+          if (dt) attrs.data_testid = dt;
+
+          if (rawTag === "a") {
+            const href = (el.href || el.getAttribute("href") || "").trim();
+            if (href) attrs.href = href;
+          }
+
+          if (Object.keys(attrs).length) node.attrs = attrs;
+        }
+
+        if (children.length) node.children = children;
+        return maybeHoistInlineText(collapseWrappers(node));
+      }
+
+      const extractedAt = new Date().toISOString();
+      const url = String(location.href || "");
+      const title = String(document.title || "");
+
+      const root = document.body ? build(document.body, 0) : null;
+      return {
+        extracted_at: extractedAt,
+        url,
+        title,
+        hostname: location.hostname,
+        visible_tree: root,
+        truncated,
+        stats: { nodes: nodeCount },
+      };
+    },
+  });
+  return result;
+}
+
+async function postScreenshot(endpoint, payload) {
+  const r = await fetch(endpoint, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify(payload),
+  });
+  const text = await r.text();
+  let data = null;
+  try {
+    data = JSON.parse(text);
+  } catch {
+    // ignore
+  }
+  if (!r.ok) {
+    throw new Error(`HTTP ${r.status}: ${text}`);
+  }
+  return data;
+}
+
+async function ping(endpoint) {
+  const base = endpoint.replace(/\/screenshot\s*$/, "");
+  const r = await fetch(`${base}/health`, { method: "GET" });
+  if (!r.ok) return `HTTP ${r.status}`;
+  const j = await r.json();
+  return j && j.ok ? "ok" : "unexpected_response";
+}
+
+async function main() {
+  const endpointEl = $("endpoint");
+  const extraEl = $("extra_instructions");
+  const captureBtn = $("capture");
+  const pingBtn = $("ping");
+  const historySel = $("history");
+  const showHistoryBtn = $("show_history");
+  const clearHistoryBtn = $("clear_history");
+
+  endpointEl.value = (await storageGet("endpoint")) || DEFAULT_ENDPOINT;
+  extraEl.value = (await storageGet(EXTRA_INSTRUCTIONS_KEY)) || "";
+  await refreshHistoryUI();
+
+  endpointEl.addEventListener("change", async () => {
+    await storageSet({ endpoint: endpointEl.value.trim() });
+  });
+  extraEl.addEventListener("change", async () => {
+    await storageSet({ [EXTRA_INSTRUCTIONS_KEY]: extraEl.value });
+  });
+
+  pingBtn.addEventListener("click", async () => {
+    const endpoint = endpointEl.value.trim() || DEFAULT_ENDPOINT;
+    setStatus("Pinging...", "");
+    const msg = await ping(endpoint);
+    setStatus(`Ping result: ${msg}`, msg === "ok" ? "ok" : "err");
+  });
+
+  showHistoryBtn.addEventListener("click", async () => {
+    const history = await loadHistory();
+    if (!history.length) {
+      setStatus("History is empty.", "err");
+      return;
+    }
+    const id = historySel.value;
+    const item = history.find((x) => (x.id || x.png_path || x.meta_path) === id) || history[0];
+    if (!item) {
+      setStatus("No history item selected.", "err");
+      return;
+    }
+    setStatus(renderResult(item), "ok");
+  });
+
+  clearHistoryBtn.addEventListener("click", async () => {
+    await saveHistory([]);
+    await refreshHistoryUI();
+    setStatus("History cleared.", "ok");
+  });
+
+  captureBtn.addEventListener("click", async () => {
+    const endpoint = endpointEl.value.trim() || DEFAULT_ENDPOINT;
+    const extraInstructions = (extraEl.value || "").trim();
+    captureBtn.disabled = true;
+    setStatus("Extracting page content...", "");
+
+    try {
+      const tab = await getActiveTab();
+      if (!tab) throw new Error("No active tab found");
+
+      let content = null;
+      try {
+        content = await extractPageContent(tab.id);
+      } catch (e) {
+        // Some URLs (chrome://*, Web Store, PDF viewer) cannot be scripted.
+        content = { error: String(e && e.message ? e.message : e) };
+      }
+
+      setStatus("Capturing visible tab...", "");
+      const dataUrl = await captureVisibleTab();
+      setStatus("Uploading to local server...", "");
+
+      const resp = await postScreenshot(endpoint, {
+        data_url: dataUrl,
+        title: tab.title || "",
+        url: tab.url || "",
+        ts: new Date().toISOString(),
+        content,
+        extra_instructions: extraInstructions,
+      });
+
+      // Persist for later viewing in the popup.
+      const history = await loadHistory();
+      const entry = {
+        id: resp.png_path || resp.meta_path || String(Date.now()),
+        saved_at: new Date().toISOString(),
+        title: tab.title || "",
+        url: tab.url || "",
+        extra_instructions: extraInstructions,
+        resp: {
+          png_path: resp.png_path || "",
+          meta_path: resp.meta_path || "",
+          content_path: resp.content_path || "",
+          ai_result: resp.ai_result || null,
+        },
+      };
+      const deduped = [entry, ...history.filter((x) => (x.id || x.png_path || x.meta_path) !== entry.id)].slice(0, HISTORY_LIMIT);
+      await saveHistory(deduped);
+      await refreshHistoryUI();
+
+      setStatus(renderResult(entry), "ok");
+    } catch (e) {
+      setStatus(String(e && e.message ? e.message : e), "err");
+    } finally {
+      captureBtn.disabled = false;
+    }
+  });
+}
+
+main();
diff --git a/aiea/requirements.txt b/aiea/requirements.txt
new file mode 100644
index 0000000..5a8d75f
--- /dev/null
+++ b/aiea/requirements.txt
@@ -0,0 +1,2 @@
+openai>=1.0.0
+
diff --git a/aiea/scripts/ai_prepare_responses.py b/aiea/scripts/ai_prepare_responses.py
new file mode 100644
index 0000000..501e8aa
--- /dev/null
+++ b/aiea/scripts/ai_prepare_responses.py
@@ -0,0 +1,295 @@
+#!/usr/bin/env python3
+import argparse
+import base64
+import json
+import os
+import re
+import sys
+from pathlib import Path
+
+
+def _load_dotenv_if_present(project_root: Path) -> None:
+    """
+    Minimal .env loader:
+    - supports KEY=VALUE
+    - ignores blank lines and lines starting with '#'
+    - does not support quotes/escapes; keep it simple
+    """
+    if os.getenv("OPENAI_API_KEY"):
+        return
+
+    p = project_root / ".env"
+    if not p.exists():
+        return
+
+    try:
+        for line in p.read_text("utf-8").splitlines():
+            s = line.strip()
+            if not s or s.startswith("#") or "=" not in s:
+                continue
+            k, v = s.split("=", 1)
+            k = k.strip()
+            v = v.strip()
+            if k and v and k not in os.environ:
+                os.environ[k] = v
+    except Exception:
+        return
+
+
+def _read_json(path: Path) -> dict:
+    return json.loads(path.read_text("utf-8"))
+
+
+def _data_url_for_png(png_path: Path) -> str:
+    b64 = base64.b64encode(png_path.read_bytes()).decode("ascii")
+    return f"data:image/png;base64,{b64}"
+
+
+def _truncate_text(s: str, max_chars: int) -> str:
+    if len(s) <= max_chars:
+        return s
+    return s[: max_chars - 1] + "\u2026"
+
+
+def _safe_json_dump(obj: object, max_chars: int) -> str:
+    s = json.dumps(obj, ensure_ascii=True, separators=(",", ":"), sort_keys=False)
+    return _truncate_text(s, max_chars)
+
+def _ea_sanitize_text(text: object) -> str:
+    if text is None:
+        return ""
+    s = str(text)
+    if s == "":
+        return ""
+
+    s = s.replace("\r", "").replace("\t", "    ")
+
+    replacements = {
+        "\u201c": '"',
+        "\u201d": '"',
+        "\u201e": '"',
+        "\u201f": '"',
+        "\u2018": "'",
+        "\u2019": "'",
+        "\u201a": "'",
+        "\u201b": "'",
+        "\u2014": "-",
+        "\u2013": "-",
+        "\u2212": "-",
+        "\u2022": "- ",
+        "\u2026": "...",
+    }
+    for k, v in replacements.items():
+        s = s.replace(k, v)
+
+    s = re.sub(
+        r"[\u00A0\u2000-\u200A\u202F\u205F\u3000\u1680\u180E\u2800\u3164\uFFA0]",
+        " ",
+        s,
+    )
+    s = s.replace("\u2028", "\n").replace("\u2029", "\n\n")
+    s = re.sub(
+        r"[\u200B\u200C\u200D\u200E\u200F\u202A-\u202E\u2060\u2061\u2066-\u2069\u206A-\u206F\u00AD\u034F\u115F\u1160\u17B4\u17B5\u180B-\u180D\uFE00-\uFE0F\uFEFF\u001C\u000C]",
+        "",
+        s,
+    )
+    s = s.replace("\u2062", "x").replace("\u2063", ",").replace("\u2064", "+")
+    s = re.sub(r"[ ]{2,}", " ", s)
+    s = re.sub(r"\n{3,}", "\n\n", s)
+    return s.lower()
+
+
+def _sanitize_ai_payload(ai: dict, page_url: str, page_title: str) -> dict:
+    out = dict(ai) if isinstance(ai, dict) else {}
+    out["page_url"] = page_url
+    out["page_title"] = page_title
+    out["notes"] = _ea_sanitize_text(out.get("notes", ""))
+
+    posts = out.get("posts", [])
+    if not isinstance(posts, list):
+        posts = []
+    cleaned_posts = []
+    for i, p in enumerate(posts):
+        if not isinstance(p, dict):
+            continue
+        cleaned_posts.append(
+            {
+                "index": int(p.get("index", i)),
+                "post_text": _ea_sanitize_text(p.get("post_text", "")),
+                "improved_short": _ea_sanitize_text(p.get("improved_short", "")),
+                "improved_medium": _ea_sanitize_text(p.get("improved_medium", "")),
+                "critical_short": _ea_sanitize_text(p.get("critical_short", "")),
+                "critical_medium": _ea_sanitize_text(p.get("critical_medium", "")),
+                "suggested_short": _ea_sanitize_text(p.get("suggested_short", "")),
+                "suggested_medium": _ea_sanitize_text(p.get("suggested_medium", "")),
+            }
+        )
+    out["posts"] = cleaned_posts
+    return out
+
+
+def _response_schema(max_posts: int) -> dict:
+    # Keep schema simple; strict mode supports a subset of JSON Schema.
+    return {
+        "type": "object",
+        "additionalProperties": False,
+        "properties": {
+            "page_url": {"type": "string"},
+            "page_title": {"type": "string"},
+            "posts": {
+                "type": "array",
+                "maxItems": max_posts,
+                "items": {
+                    "type": "object",
+                    "additionalProperties": False,
+                    "properties": {
+                        "index": {"type": "integer"},
+                        "post_text": {"type": "string"},
+                        "improved_short": {"type": "string"},
+                        "improved_medium": {"type": "string"},
+                        "critical_short": {"type": "string"},
+                        "critical_medium": {"type": "string"},
+                        "suggested_short": {"type": "string"},
+                        "suggested_medium": {"type": "string"},
+                    },
+                    "required": [
+                        "index",
+                        "post_text",
+                        "improved_short",
+                        "improved_medium",
+                        "critical_short",
+                        "critical_medium",
+                        "suggested_short",
+                        "suggested_medium",
+                    ],
+                },
+            },
+            "notes": {"type": "string"},
+        },
+        # OpenAI strict json_schema currently expects all top-level properties to be required.
+        "required": ["page_url", "page_title", "posts", "notes"],
+    }
+
+
+def main(argv: list[str]) -> int:
+    p = argparse.ArgumentParser(
+        description="Use OpenAI to draft short + medium responses per visible post on the page (screenshot + extracted content)."
+    )
+    p.add_argument("png_path", help="Path to saved screenshot PNG")
+    p.add_argument("meta_path", help="Path to saved meta JSON")
+    p.add_argument("content_path", nargs="?", default="", help="Optional path to saved extracted content JSON")
+    p.add_argument("--model", default=os.getenv("AI_EA_MODEL", "gpt-5.2"))
+    p.add_argument("--max-posts", type=int, default=int(os.getenv("AI_EA_MAX_POSTS", "12")))
+    p.add_argument("--out", default="", help="Output path (default: alongside PNG, with .ai.json suffix)")
+    p.add_argument("--content-max-chars", type=int, default=120_000, help="Max chars of content JSON sent to the model")
+    p.add_argument("--image-detail", default="auto", choices=["low", "high", "auto"])
+    args = p.parse_args(argv)
+
+    project_root = Path(__file__).resolve().parents[1]
+    _load_dotenv_if_present(project_root)
+
+    try:
+        from openai import OpenAI  # type: ignore
+    except Exception:
+        print("Missing dependency: pip install openai", file=sys.stderr)
+        return 2
+
+    if not os.getenv("OPENAI_API_KEY"):
+        print("OPENAI_API_KEY is not set (export it or put it in .env). Skipping.", file=sys.stderr)
+        return 3
+
+    png_path = Path(args.png_path).expanduser().resolve()
+    meta_path = Path(args.meta_path).expanduser().resolve()
+    content_path = Path(args.content_path).expanduser().resolve() if args.content_path else None
+
+    meta = _read_json(meta_path)
+    content = _read_json(content_path) if (content_path and content_path.exists()) else None
+
+    instructions_path = project_root / "AI_EA_INSTRUCTIONS.MD"
+    system_instructions = instructions_path.read_text("utf-8") if instructions_path.exists() else ""
+
+    page_url = str(meta.get("url") or "")
+    page_title = str(meta.get("title") or "")
+    extra_instructions = str(meta.get("extra_instructions") or "").strip()
+
+    user_payload = {
+        "page_url": page_url,
+        "page_title": page_title,
+        "meta": meta,
+        "content": content,
+        "task": {
+            "goal": "Draft replies to each distinct post currently visible on the page.",
+            "definition_of_post": "A single feed item / post / story / comment root visible on-screen right now. If it's a single-article page, treat the main article as one post.",
+            "output_requirements": {
+                #"ironic": "Lightly ironic, laughing at us humans (not cruel).",
+                "improved": "Proofread whatever is given in extra_instructions [EXTRA_INSTRUCTIONS]!!!  Proofreading-style improvements, preserving the original words as much as possible. Improving in medium version.",
+                "critical": "Bold/critical: politely questions the premise or assumptions.",
+                "suggested": "Best style you think fits (helpful/witty/clarifying/etc).",
+                "short": "direct, useful, no fluff. if X(twitter): 1-2 sentences max, if Reddit: 3-6 sentences max.",
+                "medium": "more context, still concise. if X(twitter): 3-6 sentences max, if Reddit: 6-12 sentences max.",
+                "style": "Follow the system instructions for voice/tone. Apply EXTRA_INSTRUCTIONS to all responses. If unclear what the post says, be honest and ask a question instead of guessing.",
+            },
+        },
+    }
+
+    prompt_text = (
+        "You will receive (1) a screenshot of the current viewport and (2) extracted visible page content.\n"
+        "Identify each distinct post visible on the page and draft SIX reply options per post:\n"
+        "- improved_short, improved_medium\n"
+        "- critical_short, critical_medium\n"
+        "- suggested_short, suggested_medium\n"
+        "All six must follow the system instructions and EXTRA_INSTRUCTIONS.\n"
+        "Do not invent facts not present in the screenshot/content.\n"
+        "Return JSON matching the provided schema. Include all top-level keys: page_url, page_title, posts, notes.\n"
+        "If a value is unknown, use an empty string.\n\n"
+        + (f"EXTRA_INSTRUCTIONS={extra_instructions}\n\n" if extra_instructions else "")
+        + f"PAGE_DATA_JSON={_safe_json_dump(user_payload, args.content_max_chars)}"
+    )
+
+    # Screenshot is provided as a base64 data URL image input.
+    image_data_url = _data_url_for_png(png_path)
+
+    client = OpenAI()
+
+    resp = client.responses.create(
+        model=args.model,
+        instructions=system_instructions,
+        input=[
+            {
+                "role": "user",
+                "content": [
+                    {"type": "input_text", "text": prompt_text},
+                    {"type": "input_image", "image_url": image_data_url, "detail": args.image_detail},
+                ],
+            }
+        ],
+        text={
+            "format": {
+                "type": "json_schema",
+                "name": "ea_post_responses",
+                "description": "Draft short and medium replies for each visible post on the page.",
+                "schema": _response_schema(args.max_posts),
+                "strict": True,
+            },
+            "verbosity": "low",
+        },
+        max_output_tokens=1400,
+    )
+
+    raw = resp.output_text or ""
+    try:
+        parsed = json.loads(raw)
+    except Exception:
+        parsed = {"error": "non_json_output", "raw": raw}
+
+    if isinstance(parsed, dict) and "posts" in parsed:
+        parsed = _sanitize_ai_payload(parsed, page_url=page_url, page_title=page_title)
+
+    out_path = Path(args.out) if args.out else png_path.with_suffix(".ai.json")
+    out_path.write_text(json.dumps(parsed, indent=2, ensure_ascii=True) + "\n", encoding="utf-8")
+    print(str(out_path))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main(sys.argv[1:]))
diff --git a/aiea/scripts/on_screenshot.sh b/aiea/scripts/on_screenshot.sh
new file mode 100644
index 0000000..e37544f
--- /dev/null
+++ b/aiea/scripts/on_screenshot.sh
@@ -0,0 +1,18 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+png_path="${1:?png_path missing}"
+meta_path="${2:?meta_path missing}"
+content_path="${3:-}"
+
+echo "Saved PNG:  ${png_path}"
+echo "Saved META: ${meta_path}"
+if [[ -n "${content_path}" ]]; then
+  echo "Saved CONTENT: ${content_path}"
+fi
+
+if [[ -n "${OPENAI_API_KEY:-}" ]] || [[ -f ".env" ]]; then
+  python3 scripts/ai_prepare_responses.py "$png_path" "$meta_path" "${content_path}"
+else
+  echo "OPENAI_API_KEY not set (and no .env). Skipping OpenAI step."
+fi
diff --git a/aiea/tools/local_screenshot_bridge.py b/aiea/tools/local_screenshot_bridge.py
new file mode 100644
index 0000000..defce21
--- /dev/null
+++ b/aiea/tools/local_screenshot_bridge.py
@@ -0,0 +1,837 @@
+#!/usr/bin/env python3
+import argparse
+import base64
+import json
+import os
+import re
+import subprocess
+import sys
+import time
+import traceback
+from datetime import datetime, timezone
+from http.server import BaseHTTPRequestHandler, HTTPServer
+from pathlib import Path
+from typing import Optional
+
+
+_LOG_LEVELS = {"debug": 10, "info": 20, "error": 40, "quiet": 100}
+
+
+def _log(server, level: str, msg: str) -> None:
+    """
+    Minimal structured-ish logging to stderr.
+
+    server.log_level: debug|info|error|quiet (default: info)
+    """
+    try:
+        configured = getattr(server, "log_level", "info") if server is not None else "info"
+        configured_rank = _LOG_LEVELS.get(str(configured).lower(), _LOG_LEVELS["info"])
+        level_rank = _LOG_LEVELS.get(str(level).lower(), _LOG_LEVELS["info"])
+        if level_rank < configured_rank:
+            return
+        ts = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
+        print(f"[{ts}] {level.upper()}: {msg}", file=sys.stderr)
+    except Exception:
+        # Never let logging break the handler.
+        return
+
+
+def _slug(s: str, max_len: int = 80) -> str:
+    s = (s or "").strip().lower()
+    s = re.sub(r"[^a-z0-9]+", "-", s)
+    s = s.strip("-")
+    if not s:
+        return "screenshot"
+    return s[:max_len]
+
+def _load_dotenv_if_present(project_root: Path) -> None:
+    """
+    Minimal .env loader:
+    - supports KEY=VALUE
+    - ignores blank lines and lines starting with '#'
+    - does not support quotes/escapes
+    """
+    if os.getenv("OPENAI_API_KEY"):
+        return
+
+    p = project_root / ".env"
+    if not p.exists():
+        return
+
+    try:
+        for line in p.read_text("utf-8").splitlines():
+            s = line.strip()
+            if not s or s.startswith("#") or "=" not in s:
+                continue
+            k, v = s.split("=", 1)
+            k = k.strip()
+            v = v.strip()
+            if k and v and k not in os.environ:
+                os.environ[k] = v
+    except Exception:
+        return
+
+
+def _truncate(s: str, max_chars: int) -> str:
+    if len(s) <= max_chars:
+        return s
+    return s[: max_chars - 1] + "\u2026"
+
+
+def _safe_json_dump(obj: object, max_chars: int) -> str:
+    s = json.dumps(obj, ensure_ascii=True, separators=(",", ":"), sort_keys=False)
+    return _truncate(s, max_chars)
+
+
+def _maybe_dump_model(obj: object) -> Optional[dict]:
+    """
+    Best-effort conversion of SDK model objects (pydantic-ish) to plain dicts.
+    """
+    if obj is None:
+        return None
+    for attr in ("model_dump", "dict", "to_dict"):
+        fn = getattr(obj, attr, None)
+        if callable(fn):
+            try:
+                out = fn()
+                return out if isinstance(out, dict) else None
+            except Exception:
+                continue
+    return None
+
+
+def _extract_json_text(raw: str) -> Optional[str]:
+    """
+    Best-effort extraction of a JSON object from a text response.
+
+    Some providers occasionally wrap JSON in code fences or add preamble text.
+    We keep this conservative; if it can't be extracted, we return None.
+    """
+    if not raw:
+        return None
+
+    # ```json ... ``` or any fenced block: ```...```
+    # We capture the whole fenced body (not just {...}) so nested braces don't break extraction.
+    m = re.search(r"```(?:[a-z0-9_+-]+)?\s*(.*?)\s*```", raw, flags=re.DOTALL | re.IGNORECASE)
+    if m:
+        return m.group(1).strip()
+
+    # First {...last} span
+    start = raw.find("{")
+    end = raw.rfind("}")
+    if start != -1 and end != -1 and end > start:
+        return raw[start : end + 1].strip()
+
+    return None
+
+
+def _ai_error_payload(
+    *,
+    error: str,
+    detail: str = "",
+    raw: str = "",
+    model: str = "",
+    response_id: str = "",
+    status: str = "",
+    incomplete_reason: str = "",
+    usage: Optional[dict] = None,
+    took_ms: Optional[int] = None,
+    ai_path: Optional[Path] = None,
+) -> dict:
+    payload: dict = {"ok": False, "error": error}
+    if detail:
+        payload["detail"] = detail
+    if raw:
+        payload["raw_preview"] = _truncate(raw, 2000)
+    if model:
+        payload["model"] = model
+    if response_id:
+        payload["response_id"] = response_id
+    if status:
+        payload["status"] = status
+    if incomplete_reason:
+        payload["incomplete_reason"] = incomplete_reason
+    if usage:
+        payload["usage"] = usage
+    if isinstance(took_ms, int):
+        payload["took_ms"] = took_ms
+    if ai_path is not None:
+        payload["ai_path"] = str(ai_path)
+    return payload
+
+
+def _is_valid_ai_json(parsed: object) -> bool:
+    if not isinstance(parsed, dict):
+        return False
+    posts = parsed.get("posts", None)
+    return isinstance(posts, list)
+
+
+def _ea_sanitize_text(text: object) -> str:
+    """
+    Port of fl_geo_sanitize_text(), plus lowercase output (no capitals).
+
+    Notes:
+    - stays ASCII in-code by using \\u escapes for unicode literals.
+    - preserves newlines (normalizes excess blank lines).
+    """
+    if text is None:
+        return ""
+    s = str(text)
+    if s == "":
+        return ""
+
+    # 1) Quick ASCII-level normalizations
+    s = s.replace("\r", "").replace("\t", "    ")
+
+    # 2) Specific single-char replacements
+    replacements = {
+        "\u201c": '"',  # “
+        "\u201d": '"',  # ”
+        "\u201e": '"',  # „
+        "\u201f": '"',  # ‟
+        "\u2018": "'",  # ‘
+        "\u2019": "'",  # ’
+        "\u201a": "'",  # ‚
+        "\u201b": "'",  # ‛
+        "\u2014": "-",  # —
+        "\u2013": "-",  # –
+        "\u2212": "-",  # −
+        "\u2022": "- ",  # •
+        "\u2026": "...",  # …
+    }
+    for k, v in replacements.items():
+        s = s.replace(k, v)
+
+    # 3) Regex-based replacements/removals
+    s = re.sub(
+        r"[\u00A0\u2000-\u200A\u202F\u205F\u3000\u1680\u180E\u2800\u3164\uFFA0]",
+        " ",
+        s,
+    )
+    s = s.replace("\u2028", "\n")  # LS
+    s = s.replace("\u2029", "\n\n")  # PS
+
+    s = re.sub(
+        r"[\u200B\u200C\u200D\u200E\u200F\u202A-\u202E\u2060\u2061\u2066-\u2069\u206A-\u206F\u00AD\u034F\u115F\u1160\u17B4\u17B5\u180B-\u180D\uFE00-\uFE0F\uFEFF\u001C\u000C]",
+        "",
+        s,
+    )
+
+    # Invisible math
+    s = s.replace("\u2062", "x").replace("\u2063", ",").replace("\u2064", "+")
+
+    # 4) Collapse excessive spaces
+    s = re.sub(r"[ ]{2,}", " ", s)
+
+    # 5) Normalize multiple blank lines to at most two
+    s = re.sub(r"\n{3,}", "\n\n", s)
+
+    # Remove capitals: lowercase all text.
+    return s.lower()
+
+
+def _sanitize_ai_payload(ai: dict, page_url: str, page_title: str) -> dict:
+    # Strict schema requires these keys; we prefer ground truth from meta.
+    out = dict(ai) if isinstance(ai, dict) else {}
+    out["page_url"] = page_url
+    out["page_title"] = page_title
+    out["notes"] = _ea_sanitize_text(out.get("notes", ""))
+
+    posts = out.get("posts", [])
+    if not isinstance(posts, list):
+        posts = []
+
+    cleaned_posts = []
+    for i, p in enumerate(posts):
+        if not isinstance(p, dict):
+            continue
+        cleaned_posts.append(
+            {
+                "index": int(p.get("index", i)),
+                "post_text": _ea_sanitize_text(p.get("post_text", "")),
+                "improved_short": _ea_sanitize_text(p.get("improved_short", "")),
+                "improved_medium": _ea_sanitize_text(p.get("improved_medium", "")),
+                "critical_short": _ea_sanitize_text(p.get("critical_short", "")),
+                "critical_medium": _ea_sanitize_text(p.get("critical_medium", "")),
+                "suggested_short": _ea_sanitize_text(p.get("suggested_short", "")),
+                "suggested_medium": _ea_sanitize_text(p.get("suggested_medium", "")),
+            }
+        )
+    out["posts"] = cleaned_posts
+    return out
+
+
+def _response_schema(max_posts: int) -> dict:
+    return {
+        "type": "object",
+        "additionalProperties": False,
+        "properties": {
+            "page_url": {"type": "string"},
+            "page_title": {"type": "string"},
+            "posts": {
+                "type": "array",
+                "maxItems": max_posts,
+                "items": {
+                    "type": "object",
+                    "additionalProperties": False,
+                    "properties": {
+                        "index": {"type": "integer"},
+                        "post_text": {"type": "string"},
+                        "improved_short": {"type": "string"},
+                        "improved_medium": {"type": "string"},
+                        "critical_short": {"type": "string"},
+                        "critical_medium": {"type": "string"},
+                        "suggested_short": {"type": "string"},
+                        "suggested_medium": {"type": "string"},
+                    },
+                    "required": [
+                        "index",
+                        "post_text",
+                        "improved_short",
+                        "improved_medium",
+                        "critical_short",
+                        "critical_medium",
+                        "suggested_short",
+                        "suggested_medium",
+                    ],
+                },
+            },
+            "notes": {"type": "string"},
+        },
+        # OpenAI strict json_schema currently expects all top-level properties to be required.
+        # If you don't have a value, return "" / [].
+        "required": ["page_url", "page_title", "posts", "notes"],
+    }
+
+
+def _maybe_generate_ai(server, png_path: Path, meta: dict, content: object) -> dict:
+    """
+    Returns:
+      { "ok": True, "ai": , "ai_path": , "took_ms":  }
+    or { "ok": False, "error": , "detail":  }
+    """
+    if not getattr(server, "ai_enabled", False):
+        return {"ok": False, "error": "ai_disabled"}
+
+    project_root: Path = server.project_root  # type: ignore[attr-defined]
+    _load_dotenv_if_present(project_root)
+
+    if not os.getenv("OPENAI_API_KEY"):
+        _log(server, "error", "AI disabled: missing OPENAI_API_KEY")
+        return {"ok": False, "error": "missing_openai_api_key"}
+
+    try:
+        from openai import OpenAI  # type: ignore
+    except Exception as e:
+        _log(server, "error", f"AI disabled: missing openai sdk ({type(e).__name__}: {e})")
+        return {"ok": False, "error": "missing_openai_sdk", "detail": str(e)}
+
+    instructions_text = getattr(server, "ai_instructions", "")
+    model = getattr(server, "ai_model", "gpt-5.2")
+    max_posts = int(getattr(server, "ai_max_posts", 12))
+    content_max_chars = int(getattr(server, "ai_content_max_chars", 120_000))
+    image_detail = getattr(server, "ai_image_detail", "auto")
+    max_output_tokens = int(getattr(server, "ai_max_output_tokens", 1400))
+
+    page_url = str(meta.get("url") or "")
+    page_title = str(meta.get("title") or "")
+    extra_instructions = str(meta.get("extra_instructions") or "").strip()
+
+    _log(
+        server,
+        "debug",
+        f"AI request: model={model} max_posts={max_posts} image_detail={image_detail} max_output_tokens={max_output_tokens} url={_truncate(page_url, 140)}",
+    )
+
+    user_payload = {
+        "page_url": page_url,
+        "page_title": page_title,
+        "meta": meta,
+        "content": content,
+        "task": {
+            "goal": "Draft replies to each distinct post currently visible on the page.",
+            "definition_of_post": "A single feed item / post / story / comment root visible on-screen right now. If it's a single-article page, treat the main article as one post.",
+            "output_requirements": {
+#                 "ironic": "Lightly ironic, laughing at us humans (not cruel).",
+                "improved": "Proofread whatever is given in extra_instructions [EXTRA_INSTRUCTIONS]. Proofreading-style improvements, preserving the original words as much as possible. Improving in medium version.",
+                "critical": "Bold/critical: politely questions the premise or assumptions.",
+                "suggested": "Best style you think fits (helpful/witty/clarifying/etc).",
+                "short": "direct, useful, no fluff. if X(twitter): 1-2 sentences max, if Reddit: 3-6 sentences max.",
+                "medium": "more context, still concise. if X(twitter): 3-6 sentences max, if Reddit: 6-12 sentences max.",
+                "style": "Follow the system instructions for voice/tone. Apply EXTRA_INSTRUCTIONS to all responses. If unclear what the post says, be honest and ask a question instead of guessing.",
+            },
+        },
+    }
+
+    prompt_text = (
+        "You will receive (1) a screenshot of the current viewport and (2) extracted visible page content.\n"
+        "Identify each distinct post visible on the page and draft SIX reply options per post:\n"
+        "- improved_short, improved_medium\n"
+        "- critical_short, critical_medium\n"
+        "- suggested_short, suggested_medium\n"
+        "All six must follow the system instructions and EXTRA_INSTRUCTIONS.\n"
+        "Do not invent facts not present in the screenshot/content.\n"
+        "Return JSON matching the provided schema. Include all top-level keys: page_url, page_title, posts, notes.\n"
+        "If a value is unknown, use an empty string.\n\n"
+        + (f"EXTRA_INSTRUCTIONS={extra_instructions}\n\n" if extra_instructions else "")
+        + f"PAGE_DATA_JSON={_safe_json_dump(user_payload, content_max_chars)}"
+    )
+
+    b64 = base64.b64encode(png_path.read_bytes()).decode("ascii")
+    image_data_url = f"data:image/png;base64,{b64}"
+
+    t0 = time.monotonic()
+    client = OpenAI()
+    resp = None
+    took_ms = None
+    try:
+        resp = client.responses.create(
+            model=model,
+            instructions=instructions_text,
+            input=[
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "input_text", "text": prompt_text},
+                        {"type": "input_image", "image_url": image_data_url, "detail": image_detail},
+                    ],
+                }
+            ],
+            text={
+                "format": {
+                    "type": "json_schema",
+                    "name": "ea_post_responses",
+                    "description": "Draft short and medium replies for each visible post on the page.",
+                    "schema": _response_schema(max_posts),
+                    "strict": True,
+                },
+                "verbosity": "low",
+            },
+            max_output_tokens=max_output_tokens,
+        )
+        took_ms = int((time.monotonic() - t0) * 1000)
+    except Exception as e:
+        took_ms = int((time.monotonic() - t0) * 1000)
+        tb = traceback.format_exc(limit=8)
+        detail = f"{type(e).__name__}: {e}"
+        # Some OpenAI exceptions have request id / status in attrs; include if present.
+        rid = getattr(e, "request_id", "") or getattr(getattr(e, "response", None), "headers", {}).get("x-request-id", "")
+        sc = getattr(e, "status_code", None)
+        if rid:
+            detail = f"{detail} (request_id={rid})"
+        if isinstance(sc, int):
+            detail = f"{detail} (status={sc})"
+        _log(server, "error", f"AI exception after {took_ms}ms: {detail}")
+        _log(server, "debug", f"AI traceback:\n{tb}")
+        # Still write a debug file for the screenshot for later inspection.
+        ai_path = png_path.with_suffix(".ai.json")
+        debug_obj = {
+            "error": "ai_exception",
+            "detail": detail,
+            "took_ms": took_ms,
+            "model": str(model),
+            "traceback": tb if getattr(server, "log_level", "info") == "debug" else "",
+        }
+        try:
+            ai_path.write_text(json.dumps(debug_obj, indent=2, ensure_ascii=True) + "\n", encoding="utf-8")
+        except Exception:
+            pass
+        return _ai_error_payload(
+            error="ai_exception",
+            detail=detail,
+            model=str(model),
+            response_id="",
+            status="",
+            incomplete_reason="",
+            usage=None,
+            took_ms=took_ms,
+            ai_path=ai_path,
+        )
+
+    response_id = str(getattr(resp, "id", "") or "")
+    status = str(getattr(resp, "status", "") or "")
+    incomplete_reason = ""
+    try:
+        incomplete_details = getattr(resp, "incomplete_details", None)
+        if incomplete_details is not None:
+            incomplete_reason = str(getattr(incomplete_details, "reason", "") or "")
+    except Exception:
+        incomplete_reason = ""
+    usage = _maybe_dump_model(getattr(resp, "usage", None))
+
+    _log(
+        server,
+        "debug",
+        f"AI response meta: status={status or '?'} incomplete_reason={incomplete_reason or '(none)'} usage={_safe_json_dump(usage or {}, 800)} response_id={response_id}",
+    )
+
+    raw = ""
+    try:
+        raw = resp.output_text or ""
+    except Exception:
+        raw = ""
+    _log(server, "debug", f"AI output_text chars={len(raw)} response_id={response_id}")
+
+    parsed: object
+    parse_error = ""
+    parse_detail = ""
+    try:
+        parsed = json.loads(raw)
+    except Exception as e:
+        # Try a couple conservative extraction heuristics.
+        candidate = _extract_json_text(raw)
+        if candidate:
+            try:
+                parsed = json.loads(candidate)
+            except Exception as e2:
+                parse_error = "non_json_output"
+                parse_detail = f"{type(e2).__name__}: {e2}"
+                parsed = {"error": "non_json_output", "raw": raw}
+        else:
+            parse_error = "non_json_output"
+            parse_detail = f"{type(e).__name__}: {e}"
+            parsed = {"error": "non_json_output", "raw": raw}
+
+    if parse_error:
+        _log(server, "error", f"AI output parse failed: {parse_error} ({parse_detail}) response_id={response_id}")
+
+    if isinstance(parsed, dict) and "posts" in parsed:
+        parsed = _sanitize_ai_payload(parsed, page_url=page_url, page_title=page_title)
+
+    ai_path = png_path.with_suffix(".ai.json")
+    try:
+        # When generation fails, persist helpful metadata along with the raw text.
+        if parse_error and isinstance(parsed, dict) and "raw" in parsed:
+            parsed = {
+                **parsed,
+                "response_id": response_id,
+                "model": str(model),
+                "status": status,
+                "incomplete_reason": incomplete_reason,
+                "usage": usage or {},
+            }
+        ai_path.write_text(json.dumps(parsed, indent=2, ensure_ascii=True) + "\n", encoding="utf-8")
+    except Exception as e:
+        _log(server, "error", f"Failed writing AI file {ai_path}: {type(e).__name__}: {e}")
+
+    # If we didn't get schema-conformant output, treat it as an error so the popup doesn't show "unknown".
+    if not _is_valid_ai_json(parsed):
+        err = parse_error or (parsed.get("error", "") if isinstance(parsed, dict) else "") or "invalid_ai_output"
+        detail = parse_detail or "AI returned JSON that does not match the expected schema (missing posts[])."
+        if incomplete_reason:
+            err = incomplete_reason if incomplete_reason in ("max_output_tokens", "content_filter") else err
+            if incomplete_reason == "max_output_tokens":
+                detail = (
+                    f"AI response was truncated (incomplete_reason=max_output_tokens). "
+                    f"Try increasing --ai-max-output-tokens (currently {max_output_tokens}) or decreasing --ai-max-posts (currently {max_posts}). "
+                    f"Original parse error: {parse_detail or '(none)'}"
+                )
+            else:
+                detail = f"AI response incomplete (incomplete_reason={incomplete_reason}). Parse error: {parse_detail or '(none)'}"
+        _log(server, "error", f"AI output invalid: error={err} response_id={response_id} ai_path={ai_path}")
+        return _ai_error_payload(
+            error=str(err),
+            detail=str(detail),
+            raw=raw,
+            model=str(model),
+            response_id=response_id,
+            status=status,
+            incomplete_reason=incomplete_reason,
+            usage=usage,
+            took_ms=took_ms,
+            ai_path=ai_path,
+        )
+
+    posts_count = len(parsed.get("posts", [])) if isinstance(parsed, dict) else 0
+    _log(server, "info", f"AI ok: posts={posts_count} took_ms={took_ms} response_id={response_id} ai_path={ai_path}")
+    return {
+        "ok": True,
+        "ai": parsed,
+        "ai_path": str(ai_path),
+        "took_ms": took_ms,
+        "response_id": response_id,
+        "model": str(model),
+        "status": status,
+        "incomplete_reason": incomplete_reason,
+        "usage": usage,
+    }
+
+
+class Handler(BaseHTTPRequestHandler):
+    server_version = "LocalScreenshotBridge/0.1"
+
+    def log_message(self, fmt: str, *args):  # noqa: N802
+        # Route default HTTP request logs through our logger (and respect --log-level).
+        try:
+            msg = fmt % args
+        except Exception:
+            msg = fmt
+        try:
+            ip = self.client_address[0] if getattr(self, "client_address", None) else "?"
+        except Exception:
+            ip = "?"
+        _log(self.server, "debug", f"HTTP {ip} {msg}")  # type: ignore[arg-type]
+
+    def _send_json(self, status: int, payload: dict):
+        body = json.dumps(payload, ensure_ascii=True).encode("utf-8")
+        self.send_response(status)
+        self.send_header("Content-Type", "application/json; charset=utf-8")
+        self.send_header("Content-Length", str(len(body)))
+        # Chrome extension fetch() to localhost will preflight; allow it.
+        self.send_header("Access-Control-Allow-Origin", "*")
+        self.send_header("Access-Control-Allow-Methods", "POST, OPTIONS")
+        self.send_header("Access-Control-Allow-Headers", "Content-Type")
+        self.end_headers()
+        self.wfile.write(body)
+
+    def do_GET(self):  # noqa: N802
+        if self.path not in ("/", "/health"):
+            self._send_json(404, {"ok": False, "error": "not_found"})
+            return
+        self._send_json(
+            200,
+            {
+                "ok": True,
+                "service": "local_screenshot_bridge",
+                "out_dir": str(self.server.out_dir),  # type: ignore[attr-defined]
+                "has_run_cmd": bool(getattr(self.server, "run_cmd", None)),  # type: ignore[attr-defined]
+                "ai_enabled": bool(getattr(self.server, "ai_enabled", False)),  # type: ignore[attr-defined]
+            },
+        )
+
+    def do_OPTIONS(self):  # noqa: N802
+        self.send_response(204)
+        self.send_header("Access-Control-Allow-Origin", "*")
+        self.send_header("Access-Control-Allow-Methods", "POST, OPTIONS")
+        self.send_header("Access-Control-Allow-Headers", "Content-Type")
+        self.end_headers()
+
+    def do_POST(self):  # noqa: N802
+        if self.path != "/screenshot":
+            self._send_json(404, {"ok": False, "error": "not_found"})
+            return
+
+        try:
+            length = int(self.headers.get("Content-Length", "0"))
+        except ValueError:
+            self._send_json(400, {"ok": False, "error": "bad_content_length"})
+            return
+
+        raw = self.rfile.read(length)
+        try:
+            req = json.loads(raw.decode("utf-8"))
+        except Exception:
+            self._send_json(400, {"ok": False, "error": "bad_json"})
+            return
+
+        data_url = req.get("data_url") or ""
+        title = req.get("title") or ""
+        page_url = req.get("url") or ""
+        client_ts = req.get("ts") or ""
+        content = req.get("content", None)
+        extra_instructions = req.get("extra_instructions") or ""
+
+        extra_s = str(extra_instructions).strip()
+        if extra_s:
+            extra_s = _truncate(extra_s.replace("\r", " ").replace("\n", " "), 140)
+            extra_part = f" extra={extra_s}"
+        else:
+            extra_part = ""
+        _log(
+            self.server,  # type: ignore[arg-type]
+            "info",
+            f"Capture received: title={_truncate(str(title), 80)} url={_truncate(str(page_url), 140)} content={'yes' if content is not None else 'no'}{extra_part}",
+        )
+
+        m = re.match(r"^data:image/png;base64,(.*)$", data_url)
+        if not m:
+            self._send_json(400, {"ok": False, "error": "expected_png_data_url"})
+            return
+
+        try:
+            png_bytes = base64.b64decode(m.group(1), validate=True)
+        except Exception:
+            self._send_json(400, {"ok": False, "error": "bad_base64"})
+            return
+
+        now = datetime.now(timezone.utc)
+        stamp = now.strftime("%Y%m%dT%H%M%SZ")
+        base = f"{stamp}-{_slug(title)}"
+
+        out_dir: Path = self.server.out_dir  # type: ignore[attr-defined]
+        out_dir.mkdir(parents=True, exist_ok=True)
+        png_path = out_dir / f"{base}.png"
+        meta_path = out_dir / f"{base}.json"
+        content_path = out_dir / f"{base}.content.json"
+
+        try:
+            png_path.write_bytes(png_bytes)
+
+            # Save extracted page content separately to keep the meta file small/handy.
+            wrote_content = False
+            if content is not None:
+                try:
+                    raw_content = json.dumps(content, ensure_ascii=True, indent=2) + "\n"
+                    # Prevent pathological payloads from creating huge files.
+                    if len(raw_content.encode("utf-8")) > 2_000_000:
+                        content = {
+                            "error": "content_too_large_truncated",
+                            "note": "Original extracted content exceeded 2MB.",
+                        }
+                        raw_content = json.dumps(content, ensure_ascii=True, indent=2) + "\n"
+                    content_path.write_text(raw_content, encoding="utf-8")
+                    wrote_content = True
+                except Exception:
+                    _log(self.server, "error", f"Failed writing content file {content_path}")  # type: ignore[arg-type]
+                    # Don't fail the whole request if content writing fails.
+                    wrote_content = False
+
+            final_content_path = str(content_path) if wrote_content else None
+
+            meta_path.write_text(
+                json.dumps(
+                    {
+                        "title": title,
+                        "url": page_url,
+                        "client_ts": client_ts,
+                        "saved_utc": now.isoformat(),
+                        "png_path": str(png_path),
+                        "content_path": final_content_path,
+                        "extra_instructions": extra_instructions,
+                    },
+                    indent=2,
+                    ensure_ascii=True,
+                )
+                + "\n",
+                encoding="utf-8",
+            )
+        except Exception as e:
+            self._send_json(500, {"ok": False, "error": "write_failed", "detail": str(e)})
+            return
+
+        meta_obj = {
+            "title": title,
+            "url": page_url,
+            "client_ts": client_ts,
+            "saved_utc": now.isoformat(),
+            "png_path": str(png_path),
+            "content_path": final_content_path,
+            "extra_instructions": extra_instructions,
+        }
+        _log(
+            self.server,  # type: ignore[arg-type]
+            "info",
+            f"Saved: png={png_path} meta={meta_path} content={final_content_path or '(none)'}",
+        )
+
+        run = getattr(self.server, "run_cmd", None)  # type: ignore[attr-defined]
+        ran = None
+        if run:
+            try:
+                # Pass content_path as a 3rd arg when available. This keeps hooks compatible with older 2-arg scripts.
+                args = [str(png_path), str(meta_path)]
+                if final_content_path:
+                    args.append(final_content_path)
+                proc = subprocess.run(
+                    run + args,
+                    cwd=str(self.server.project_root),  # type: ignore[attr-defined]
+                    stdout=subprocess.PIPE,
+                    stderr=subprocess.PIPE,
+                    text=True,
+                )
+                ran = {
+                    "cmd": run,
+                    "exit_code": proc.returncode,
+                    "stdout": proc.stdout[-4000:],
+                    "stderr": proc.stderr[-4000:],
+                }
+                if proc.returncode != 0:
+                    _log(self.server, "error", f"Hook failed: exit={proc.returncode} cmd={' '.join(run)}")  # type: ignore[arg-type]
+            except Exception as e:
+                ran = {"cmd": run, "error": str(e)}
+                _log(self.server, "error", f"Hook exception: {type(e).__name__}: {e}")  # type: ignore[arg-type]
+
+        ai_result = None
+        if getattr(self.server, "ai_enabled", False):  # type: ignore[attr-defined]
+            try:
+                ai_result = _maybe_generate_ai(self.server, png_path, meta_obj, content)
+            except Exception as e:
+                detail = f"{type(e).__name__}: {e}"
+                _log(self.server, "error", f"AI exception (outer): {detail}")  # type: ignore[arg-type]
+                _log(self.server, "debug", f"AI outer traceback:\n{traceback.format_exc(limit=8)}")  # type: ignore[arg-type]
+                ai_result = {"ok": False, "error": "ai_exception", "detail": detail}
+
+        self._send_json(
+            200,
+            {
+                "ok": True,
+                "png_path": str(png_path),
+                "meta_path": str(meta_path),
+                "content_path": final_content_path,
+                "ran": ran,
+                "ai_result": ai_result,
+            },
+        )
+
+
+def main(argv: list[str]) -> int:
+    p = argparse.ArgumentParser(description="Receive screenshots from a Chrome extension and save into this project.")
+    p.add_argument("--port", type=int, default=8765)
+    p.add_argument("--bind", default="127.0.0.1", help="Bind address (default: 127.0.0.1)")
+    p.add_argument("--out-dir", default="screenshots", help="Output directory relative to project root")
+    p.add_argument("--ai", action="store_true", help="Run OpenAI to generate reply suggestions and return them to the extension")
+    p.add_argument(
+        "--log-level",
+        default=os.getenv("AIEA_LOG_LEVEL", "info"),
+        choices=sorted(_LOG_LEVELS.keys()),
+        help="Logging verbosity: debug|info|error|quiet (env: AIEA_LOG_LEVEL)",
+    )
+    p.add_argument("--ai-model", default=os.getenv("AI_EA_MODEL", "gpt-5.2"))
+    p.add_argument("--ai-max-posts", type=int, default=int(os.getenv("AI_EA_MAX_POSTS", "12")))
+    p.add_argument("--ai-content-max-chars", type=int, default=int(os.getenv("AI_EA_CONTENT_MAX_CHARS", "120000")))
+    p.add_argument("--ai-image-detail", default=os.getenv("AI_EA_IMAGE_DETAIL", "auto"))
+    p.add_argument("--ai-max-output-tokens", type=int, default=int(os.getenv("AI_EA_MAX_OUTPUT_TOKENS", "1400")))
+    p.add_argument(
+        "--run",
+        nargs="+",
+        default=None,
+        help="Optional command to run after saving. Args appended:   [content_path].",
+    )
+    args = p.parse_args(argv)
+
+    project_root = Path(__file__).resolve().parents[1]
+    out_dir = (project_root / args.out_dir).resolve()
+    if args.ai:
+        _load_dotenv_if_present(project_root)
+    instructions_path = project_root / "AI_EA_INSTRUCTIONS.MD"
+    ai_instructions = instructions_path.read_text("utf-8") if instructions_path.exists() else ""
+
+    httpd = HTTPServer((args.bind, args.port), Handler)
+    httpd.project_root = project_root  # type: ignore[attr-defined]
+    httpd.out_dir = out_dir  # type: ignore[attr-defined]
+    httpd.run_cmd = args.run  # type: ignore[attr-defined]
+    httpd.ai_enabled = bool(args.ai)  # type: ignore[attr-defined]
+    httpd.log_level = args.log_level  # type: ignore[attr-defined]
+    httpd.ai_model = args.ai_model  # type: ignore[attr-defined]
+    httpd.ai_max_posts = args.ai_max_posts  # type: ignore[attr-defined]
+    httpd.ai_content_max_chars = args.ai_content_max_chars  # type: ignore[attr-defined]
+    httpd.ai_image_detail = args.ai_image_detail  # type: ignore[attr-defined]
+    httpd.ai_max_output_tokens = args.ai_max_output_tokens  # type: ignore[attr-defined]
+    httpd.ai_instructions = ai_instructions  # type: ignore[attr-defined]
+
+    print(f"Listening on http://{args.bind}:{args.port}/screenshot", file=sys.stderr)
+    print(f"Saving screenshots to {out_dir}", file=sys.stderr)
+    print(f"Log level: {args.log_level}", file=sys.stderr)
+    if args.ai:
+        print(f"OpenAI enabled: model={args.ai_model} max_posts={args.ai_max_posts}", file=sys.stderr)
+    if args.run:
+        print(f"Will run: {' '.join(args.run)}   [content_path]", file=sys.stderr)
+    try:
+        httpd.serve_forever()
+    except KeyboardInterrupt:
+        return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main(sys.argv[1:]))