agentic-search

SkillWeb & browsing

Your AI can handle web research that needs current information and sources you can verify. Once added, this skill runs deep research with Grok as its main engine, supports it with extra sources from Tavily and Firecrawl, and grounds answers in citations. It turns pages into clean Markdown, pulls exact quotes, and reorders sources so the strongest ones come first.

Available today. Use it from your connected AI after setup.

Add the skill, then give your AI a question that needs up-to-date web answers. Ask it to back its response with citations and exact quotes so you can check every claim.

Then ask your AI: use the agentic-search skill

What your AI can do with it

  • Run current web research with grounded citations
  • Discover extra sources through Tavily and Firecrawl
  • Convert web pages into clean, high-fidelity Markdown
  • Extract verbatim quotes from sources
  • Map the pages of a website using Tavily
  • Rerank sources so the strongest material rises to the top

What this skill tells your AI

The instructions your AI receives, as published by appautomaton/webmaton in skills/agentic-search/SKILL.md and read by ahel’s review.

#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).

Signals

GitHub stars
20
Forks
1
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
agentic-search
Source
github.com/appautomaton/webmaton