research-summarizer
Use when the user asks for a sourced briefing on a topic that spans multiple web sources and requires citations.
pinned to #7f8ee3cupdated 2 weeks ago
Ask your AI client: “install skills/research-summarizer”.
Requires the metahub MCP server installed in your client. Set up MCP.
mh install skills/research-summarizermetahub onboarded this repo on the author's behalf.
If you own github.com/oxbshw/LLM-Agents-Ecosystem-Handbook on GitHub, claim the listing to take over publishing. Your claim preserves the existing eval history and badges; only the curator label is replaced with verified-publisher on your next publish.
Stars
533
Last commit
2 weeks ago
Latest release
published
- #ai
- #ai-agent
- #ai-agents
- #fine-tuning
- #finetuning-llms
- #freamework
- #llm
- #llmops
- #local-development
- #mcp-server
- #memory
- #rag
- #rag-chatbot
- #voice-agent
Evaluation report
WarningsAutomated checks the publisher passed at publish time — structure, docs, safety, and whether the artifact behaves as claimed.7f8ee3c· 2 weeks ago
Documentation
41Description quality
20 words · 112 chars — "Use when the user asks for a sourced briefing on a topic that spans multiple web…"
README is present and substantial
19,199 chars · 20 sections · 2 code blocks
Tags / topics declared
14 total — ai, ai-agent, ai-agents, fine-tuning, finetuning-llms, freamework (+8)
README has usage / example sectionswarn
README has no Usage / Example / Quick start / Installation heading at any level
Add a `# Usage`, `## Quick start`, or similar section so end users can copy/paste a working invocation. Code blocks alone work too if there are several.
Homepage / docs URL declared
no homepage declared (registry will use the repo URL) — info-only, not blocking
Release history
1- releasecurrent7f8ee3cwarn2 weeks ago
Contents
When to use
- User asks "research X" / "what's the state of Y" / "summarize the literature on Z"
- The answer requires multiple sources, not one
- The user expects citations
When NOT to use
- Single-source summarization (use a plain summarize tool)
- Code search (use
repo-auditoror grep) - Opinion / recommendation requests (this skill produces neutral briefings)
Inputs
| Name | Type | Required | Notes |
|---|---|---|---|
topic | string | yes | the question to research |
depth | "shallow" | "deep" | no | default "shallow" (5–7 sources); "deep" → 10–15 |
audience | string | no | shapes vocabulary level (e.g., "executive", "engineer") |
Outputs
A Markdown file briefing.md following the structure in references/report-template.md.
Workflow
- Plan: produce 3–7 sub-questions covering breadth and depth
- Search + fetch: for each sub-question, run
web_searchthenfetch_urlfor top 2–3 hits - Cluster: group findings by claim; load
references/clustering-rules.md - Draft: fill
references/report-template.md— every claim needs a[n]citation - Validate: every citation resolves; no domain dominates (≥ 3 distinct domains for shallow, ≥ 5 for deep)
- Self-review against success criteria below
References
references/report-template.md— the output structure- (add
clustering-rules.md,domain-allowlist.mdas the skill matures)
Success criteria
- ≥ 5 sources for shallow, ≥ 10 for deep
- ≥ 3 distinct domains
- 0 unsourced claims (or all flagged
(unsourced)) - Open Questions section populated
Failure modes
- Fewer sources available than required → return partial result, flag at top
- All sources from one domain → reject, retry plan with broader scope
- Network error → fail loudly, don't fabricate
Examples
- See
references/examples/(TBD) for one shallow and one deep run
Reviews
No reviews yet. Be the first.
Related
Browser Use
🌐 Make websites accessible for AI agents. Automate tasks online with ease.
Gpt Researcher
An autonomous agent that conducts deep research on any data using any LLM providers
Guizang Ppt Skill
AI-agent Skill for generating polished HTML slide decks: editorial magazine and Swiss layouts, image prompts, social covers, and a WebGL/low-power presentation runtime.
mh install skills/research-summarizer