Borrowing it
Nothing to install: this file belongs to fulminate-io/knowledge-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fulminate-io/knowledge-mcp/main/.claude/skills/research/SKILL.mdgit clone --depth 1 https://github.com/fulminate-io/knowledge-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/fulminate-io/knowledge-mcp/research)<a href="https://agentmods.dev/skills/fulminate-io/knowledge-mcp/research"><img src="https://agentmods.dev/badge/skills/fulminate-io/knowledge-mcp/research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/fulminate-io/knowledge-mcp/research"><img src="https://agentmods.dev/badge/skills/fulminate-io/knowledge-mcp/research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.00617 |
| Opus 5.5 | $0.00025 | $0.00247 |
| Sonnet 5.5 | $0.00012 | $0.00123 |
| Haiku 4.5 | $0.00006 | $0.00062 |
Grade A, and why
research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research: $ARGUMENTS
For pipeline discipline reference /orchestrate. This skill is research-specific.
Step 0: Recall and freshness
thoughts({"operation":"recall","query":"<topic>"}) and a knowledge search
first; what the graph holds goes into the brief as leads to reproduce, never as
facts. manage({"operation":"status"}); collect if the index is behind.
Step 1: Decide the mode
$ARGUMENTSnames a ticket → VALIDATION: the researcher reproduces every premise, corrects the facts, fills the detail, stampsmetadata.validatedor reports what blocks it.- Otherwise → DISCOVERY: what exists, how it works, the existing idiom, the call graph.
Step 2: Spawn the researcher (background)
The brief is discovery-framed: the problem or the ticket, never a candidate mechanism or a solution. Per the write-a-brief rulebook it carries verbatim the user's load-bearing rules, the tree to work at, absolute paths, and the isolation rule (probes in scratch; the operator's services untouched).
Agent(subagent_type: "researcher",
prompt: "VALIDATE ticket <id> per your validation mode: reproduce every premise on <tree>, correct the facts on the ticket, fill what the draft did not know, stamp metadata.validated or report what stays unverified and what would change intent. Recall and search before every claim. Deliver the report to main.",
description: "Validate: <ticket>",
run_in_background: true)
Step 3: On return
Read the whole report. In validation mode: confirm the stamp landed by fetching the ticket; route intent changes to the user; a ticket left in draft goes back to /brainstorm with the researcher's evidence. In discovery mode: present the existing idiom, what exists, the call graph, what was decided and what is unclear, with the provenance labels intact. Findings that confirm or contradict a recorded thought charge it, citing the research node.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · -77 lines · +23 tokens per session 3add232aef04
- 2mo ago First seen · 135 lines · 39 tokens per session scan A 884d9692daa1
research is a skill published in the GitHub repository fulminate-io/knowledge-mcp (1 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 62 tokens to every session and 617 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…