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agentic-search

Skill20 starsChanged 3 months agoMITView on GitHub

Grok-primary deep research skill for source-backed web work. Use when the task needs current web research, grounded citations, supplementary Tavily/Firecrawl source discovery, high-fidelity page-to-Markdown fetch, Tavily site mapping, verbatim quote extraction, source reranking, or reusable multi-step research sessions. Use as a supplement when ordinary search results feel incomplete, thinly sourced, or need more URLs, quotes, fetched pages, or session composition; not for simple one-off facts.

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  • Other versions1 project uses a version of this.

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    Wrote their own version · 1

    1. alibaba-damo-academy/ScholarSeed★ 38same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository5 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    All scripts use PEP 723 inline deps — always invoke via uv run.

    line 19

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

agentic-search

#ScriptIntent
1scripts/agentic_search.pyResearch a topic — AI-reasoned answer with citations
2scripts/agentic_fetch.pyFull page → Markdown, no summarization
3scripts/agentic_map.pyEnumerate URLs under a site (Tavily-only)
4scripts/agentic_extract.pyVerbatim title + 2–4 quotes from a URL
5scripts/agentic_rank.pyRerank session sources by a refined query
6scripts/agentic_get_sources.pyRetrieve or list cached sessions

How to invoke

All scripts use PEP 723 inline deps — always invoke via uv run. Allow up to 3 minutes per call.

uv run scripts/agentic_search.py --query "..." [--extra-sources N] [--auto-fetch-top N] [--platform "..."]
uv run scripts/agentic_fetch.py --url "..." [--engine auto|tavily|firecrawl|grok]
uv run scripts/agentic_map.py --url "..." [--instructions "..."] [--limit N]
uv run scripts/agentic_extract.py --url "..." [--session-id S]
uv run scripts/agentic_rank.py --query "..." --session-id S
uv run scripts/agentic_get_sources.py --list | --session-id S

Session workflow

agentic_search generates a session_id persisted to disk — the connective tissue for composing steps:

agentic_search → session_id
     ├─→ agentic_rank --session-id S --query Q     (rerank in place; mutates session)
     ├─→ agentic_extract --session-id S --url U    (append verbatim quotes)
     └─→ agentic_get_sources --session-id S        (inspect full session)

Sessions survive between invocations but may be cleared on OS reboot.

Operating discipline

Load the relevant reference before composing a non-trivial query — don't load all four upfront.

  • references/search-discipline.md — two-pass methodology, citation contract, time-context heuristic. Read for research tasks.
  • references/fetch-fidelity.md — engine trade-offs, fidelity guarantees, when not to fetch. Read before presenting extracted content.
  • references/extract-and-rank.md — extract vs fetch, when to rank, session composition patterns. Read for multi-step workflows.
  • references/provider-quirks.md — env vars, provider schemas, retry policy, debugging. Read when configuring or debugging.

Failure modes

  • No GROK_API_KEY / GROK_API_URL → config error on any Grok-using script.
  • agentic_fetch --engine auto total failure → retry with --engine grok or fall back to built-in WebFetch.
  • agentic_map without TAVILY_API_KEY → hard exit.
  • agentic_rank --session-id S session expired → re-run agentic_search.
  • sources_count: 0 with non-empty content → Grok used training data; check providers_used (grok-web-search = real citations, grok = heuristic fallback).

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