firecrawl-research-patterns

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Programmatic Firecrawl usage via the public API, academic paper routing, recursive deep research, and raw corpus persistence.

AI & Automation 62 stars 9 forks Updated today MIT

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Skill Content

# Firecrawl Research Patterns Programmatic patterns for using Firecrawl in research workflows — search, scrape, route academic papers, run recursive deep research, and persist raw results for future re-analysis. **Use the public Firecrawl API. There is no self-hosted instance.** `POST https://api.firecrawl.dev/v2/scrape` answers without an API key, which covers the low-volume, occasional conversions this repo actually does. Rate limits and queueing are acceptable — do not stand up a private deployment to avoid them. For archiving AI chat conversations (ChatGPT/Gemini shares), see `Skill(gh-tools:research-archival)`. --- > **Self-Evolving Skill**: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues. ## FIRST — TodoWrite Task Templates **MANDATORY**: Select and load the appropriate template before any research work. ### Intent routing — AI chat share URLs (chatgpt / gemini / claude) AI chat share URLs (`chatgpt.com/share/*`, `chat.openai.com/share/*`, `gemini.google.com/share/*`, `g.co/gemini/share/*`, `claude.ai/share/*`, `claude.ai/chat/*`) can be processed by **either** this skill or `Skill(gh-tools:research-archival)`. Pick by **intent**, not URL pattern: | Your intent | Skill | Output ...

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Author
terrylica
Repository
terrylica/cc-skills
Created
8 months ago
Last Updated
today
Language
Shell
License
MIT

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