agentleFS
Sign inStart free
damionrashforddamionrashford/RivalSearchMCP/skills/rival-search-mcp/SKILL.md

rival-search-mcp

Skill140 starsChanged 6 months agoMITView on GitHub

Deterministic deep research via RivalSearchMCP. 9 tools: 5-engine web search (DuckDuckGo/Bing/Yahoo/Mojeek/Wikipedia), 9-platform social search (Reddit/HN/StackOverflow/Dev.to/Medium/ProductHunt/Bluesky/Lobste.rs/Lemmy), 5-source news (Google/Bing/Guardian/GDELT/DDG), 5 academic DBs (OpenAlex/CrossRef/arXiv/PubMed/EuropePMC), GitHub search, website mapping, content extraction with OCR, and research topic synthesis. No API keys required. Use when the user needs web research, competitive analysis, content discovery, or academic paper search.

1 other project uses a version of this, 1 of them edited.

Adopted by

Most recently taken up by

  • Other versions1 project uses a version of this.

    Word for word · 0

    None found.

    Edited · 1

    1. fumoctl/nix-agent-office★ 072% same

    Wrote their own version · 0

    None found.

    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

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Every tool returns deterministic, auditable output.

    line 10
  2. Distinctive:

    All tools return structured text to stdout.

    line 49

≈ “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

RivalSearchMCP

You have access to 9 research tools via the CLI at scripts/cli.py. Run all commands with uv run scripts/cli.py.

Every tool returns deterministic, auditable output. There is no in-server LLM — you're the one doing the synthesis.

How to invoke tools

uv run scripts/cli.py call-tool <tool_name> --flag value

Available tools

  • web_search — concurrent search across DuckDuckGo, Bing, Yahoo, Mojeek, Wikipedia. Use for general web queries.
  • social_search — Reddit, Hacker News, Stack Overflow, Dev.to, Medium, Product Hunt, Bluesky, Lobste.rs, Lemmy. Use for community discussions.
  • news_aggregation — Google News, Bing News, The Guardian, GDELT, DuckDuckGo News. Use for current events. Accepts --time-range day|week|month|anytime.
  • github_search — search public GitHub repos. Use for code, libraries, projects.
  • map_website — crawl a site in research / docs / map mode. Use to explore site structure or documentation.
  • content_operations — one tool, six ops (retrieve, stream, analyze, extract, score, find_conflicts). Use to get full page content, rate source quality, or surface disagreements between sources.
  • document_analysis — extract text from PDFs, Word docs, images (image OCR via EasyOCR). Use for document processing.
  • research_topic — end-to-end research workflow for a topic, combining search, content retrieval, and analysis.
  • scientific_research — OpenAlex, CrossRef, arXiv, PubMed, Europe PMC (papers) + Kaggle, HuggingFace, Dataverse, Zenodo (datasets).

When to chain tools

  • Found a URL from search? → content_operations --operation retrieve --url <url>
  • Want to assess source trust before using results? → content_operations --operation score --urls '[…]'
  • Two sources seem to disagree? → content_operations --operation find_conflicts --urls '[…]'
  • Found a PDF link? → document_analysis --url <url>
  • Need to explore a website? → map_website --url <url> --mode docs
  • Need a unified entity profile in one shot? → research_topic --mode entity --topic "OpenAI"

Tool reference

For full flags, types, and defaults for each tool, read:

  • resources/search.md — web_search, social_search, news_aggregation, github_search, map_website
  • resources/content.md — content_operations, document_analysis
  • resources/research.md — research_topic, scientific_research

Output

All tools return structured text to stdout. Errors go to stderr. Exit codes: 0 success, 1 tool error, 2 connection failed.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free