Chisle
The coding-agent plugin that bills 52% of a bare model across 20 live tasks. Terse persona + tool-output compressor + context diet.
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Replaced brittle selector scraping with API-first recon: give it a URL or a plain-English goal and it finds the JSON API behind the page, records every request as verified HAR 1.2 and exports a ready
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AI web-scraping helper in ONE Python file - drives a real Chromium (Playwright), records verified HARs, finds the JSON API behind a page, runs tasks from plain English/Bangla and stops before payment. CLI + Python + MCP + AI skill.
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AgentTrace is an AI helper module for web scraping, shipped as one Python file. An AI agent (or you) gives it a URL or a plain-language goal; it drives a real browser, captures and verifies the network traffic of every page / click / SPA route, tells you how the site should be scraped (JSON API? hydration blob? HTML list?), extracts the data, and exports reusable API clients — politely, reproducibly, with evidence.
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║ pip install playwright && python -m playwright install chromium ║
║ python agenttrace.py doctor # is everything ready? ║
║ python agenttrace.py recon <URL> # how should this site be scraped? ║
║ python agenttrace.py extract <URL> --paginate --output data.csv ║
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| # | Section | For |
|---|---|---|
| 0 | 🧭 Pilot — a whole task from plain words | start here: one command, verified result, report + script, safety model |
| 1 | 🤖 AI agents: read this first | the decision flow + golden rules |
| 2 | 📦 Install | Windows / macOS / Linux |
| 3 | 🗺️ Task → tool map | "I want to … → use …" |
| 4 | 🍳 Recipes | copy-paste solutions for common scraping jobs |
| 5 | 🐍 Python API | Session and helpers |
| 6 | ⌨️ CLI | every command, flags, exit codes |
| 7 | 🧩 Workflow configs | no-code site configs, checkpoints |
| 8 | 🔌 MCP server | use it as tools from Claude |
| 9 | 📁 What a run writes | HARs, reports, evidence |
| 10 | 🩺 Troubleshooting | error → fix |
| 11 | 🧪 Tested | how it was tested + results |
| 12 | 🧱 Inside the file | map of agenttrace.py ↔ knowledge.md |
| 13 | 🇧🇩 বাংলায় সংক্ষেপে | Bengali summary |
You say what you want. The module works out how, does it, checks every step, and hands you the answer, a report and a reusable script. English, বাংলা or a mix. No selectors, no click sequences, no wait times.
python agenttrace.py pilot "find the price of EX5" --url https://www.phanteks.store/
python agenttrace.py pilot "daraz এ গিয়ে wireless mouse খুঁজো, কার্টে যোগ করো আর চেকআউট পেজ পর্যন্ত যাও" --url https://www.daraz.com.bd/
python agenttrace.py pilot "add it to the cart and go to the payment page" --url https://shop.example --data checkout.json
python agenttrace.py plan "…" --url … # how the task is understood + the stages - no browser opens
python agenttrace.py dashboard # the same, in a local web page (127.0.0.1)
python agenttrace.py mcp --tools lite # let an AI assistant call it as tools - the cheap way (see 0.10)
Using it from an AI model? Let it call
pilot_start(goal, url, wait_s=120)once instead of browsing step by step: it gets a ~0.5 KB answer, not a conversation. Details and measured numbers in 0.10. Give the AI the guide it needs withpython agenttrace.py skill --install(0.11).
sentence ─▶ Task planner ─▶ Website observer ─▶ Action planner ─▶ Execution ─▶ Validation ─▶ Recovery ─▶ Report + script
(EN/বাংলা) Intent+stages understand(): page picks controls Session expected vs overlays, report.md/json,
+ success type, forms, price, by their words + HAR actual per scroll, screenshots, HAR,
criteria options, controls and says why stage re-observe automation_*.py
This is the beginning of the README. Read the rest at the original. Read the full README ↗