agentic-search
SkillWeb & browsingYour 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.
No other account needed.
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.
| # | Script | Intent |
|---|---|---|
| 1 | scripts/agentic_search.py | Research a topic — AI-reasoned answer with citations |
| 2 | scripts/agentic_fetch.py | Full page → Markdown, no summarization |
| 3 | scripts/agentic_map.py | Enumerate URLs under a site (Tavily-only) |
| 4 | scripts/agentic_extract.py | Verbatim title + 2–4 quotes from a URL |
| 5 | scripts/agentic_rank.py | Rerank session sources by a refined query |
| 6 | scripts/agentic_get_sources.py | Retrieve 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 autototal failure → retry with--engine grokor fall back to built-inWebFetch.agentic_mapwithoutTAVILY_API_KEY→ hard exit.agentic_rank --session-id Ssession expired → re-runagentic_search.sources_count: 0with non-emptycontent→ Grok used training data; checkproviders_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