knowledge-match

knowledge-match is a skill for Claude Code, Codex from microsoft/cat-agent-skills. It costs 162 tokens per session (2,173 once invoked), scanned A, original, MIT.

A rule-based tool that finds reusable knowledge from a completed engagement and reports the matching engine's results. It does not create summaries, invent materials, or share anything.

In plain words
What is it for?
It is for checking released records against a new engagement's scope and listing possible lessons or assets for later review.
Why use it?
It helps answer which past knowledge a new team member may use without mixing in unapproved material or unsupported claims.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one.

Good fit It is for checking released records against a new engagement's scope and listing possible lessons or assets for later review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/microsoft/cat-agent-skills/knowledge-match
About the project

microsoft/cat-agent-skills is a static website that catalogs reusable instruction sets and related packages for AI agents. People use it to search, filter, rate, and download skills for Cowork, Copilot Studio, and Scout, along with Copilot plugins and Scout automations. The catalogue entries are the skills, instructions, plugins, and settings displayed by the site.

microsoft/cat-agent-skills · 101 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add microsoft/cat-agent-skills --skill knowledge-match
Clone the repo
git clone --depth 1 https://github.com/microsoft/cat-agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for knowledge-match

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/knowledge-match/github.svg)](https://agentmods.dev/skills/microsoft/cat-agent-skills/knowledge-match)
Your own site
<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/knowledge-match"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/knowledge-match/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.

agentmods 80×15 button for knowledge-match

Your own site · 80×15
<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/knowledge-match"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/knowledge-match.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 162 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,173 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00162 $0.02173
Opus 5.5 $0.00065 $0.00869
Sonnet 5.5 $0.00032 $0.00435
Haiku 4.5 $0.00016 $0.00217

Measured yesterday against content hash f6c04cf1c6d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

knowledge-match 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 yesterday.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/contract_validate.py, scripts/knowledge_match.py, scripts/safety_text.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

submissions/engagement-mobilization-onboarding-pack/skills/knowledge-match/SKILL.md · 62 lines

How it starts

The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Knowledge Match

Purpose

Read only knowledge_record and released_assets from Closeout output (knowledge-reuse-rules.md #1.3), keep release candidates, list governed lessons as excluded until Closeout supplies written lesson text (#2.4), and score relevance deterministically.

When to use

After engagement-retrieve, when Closeout governed.json is available.

When NOT to Use

  • Closeout harvesting, sanitisation or release decisions - use engagement-closeout-knowledge-harvest.
  • Whether this joiner may access an item - use wall-check; matched items are candidates until it runs.
  • Drafting the digest prose - use pack-draft.

Inputs

scope.json and Scenario 01 governed.json (ps.engagement-closeout-knowledge-harvest.v1), plus the raw directory, staffing input and confirmed roster engagement-retrieve read: the engine re-runs scope_digest on them and refuses a scope.json that differs from the re-derivation in any field (confidentiality-and-ethical-wall-rules.md #1.4).

Steps

  1. Run python3 scripts/knowledge_match.py --scope scope.json --raw-dir <raw> --staffing <staffing.json> --confirmed-roster <raw>/confirmed-roster.csv --closeout <closeout governed.json> --wall-register <raw>/ethical-wall-register.csv --out matched.json --generated-at <YYYY-MM-DDTHH:MM:SSZ>.
  2. If the engine exits non-zero (wrong contract, missing, null or malformed knowledge_record, released_assets, knowledge_record.reusable_assets or knowledge_record.lessons (an absent list is never read as empty), wrong field types such as a string confidence or non-boolean review_required, a scope.json that fails its stage schema, carries hold evidence without its hold, or is not the document scope_digest re-derives from the raw inputs), stop and report (see Failure handling; knowledge-reuse-rules.md #1.4).
  3. Report included items with relevance_score, review_status and citations; pending_practice_review items may be referenced by title and citation only, and their summary is always the engine's fixed title-and-citation-only statement, never the Closeout description (knowledge-reuse-rules.md #2.3). An asset excluded as description_is_stage_guidance_not_written_content has no written description: its Closeout text is guidance to a drafter, so never quote, paraphrase or write a summary from it (knowledge-reuse-rules.md #2.6).
  4. Report excluded_items by ID and reason; never describe held or candidate assets. A lesson excluded as lesson_text_not_written_in_governed_closeout_record has no written lesson yet: say so with its citation, and never quote, paraphrase or write a lesson from Closeout's drafting_guidance, which is an instruction to the Closeout drafter, not lesson content (knowledge-reuse-rules.md #2.4).
  5. Hand matched.json to wall-check.

Read the full file on GitHub · 62 lines

Changes

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.

  1. yesterday First seen · 62 lines · 162 tokens per session scan A f6c04cf1c6d8

Subscribe to this mod's changes

knowledge-match is a skill published in the GitHub repository microsoft/cat-agent-skills (101 stars, last pushed yesterday), licensed MIT. It adds 162 tokens to every session and 2,173 once invoked, about $0.0006 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 2026-11-07.

Related

knowledge-match compared with skills from other repositories

knowledge-match next to 6 skills from other repositories
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knowledge-matchmicrosoft/cat-agent-skillsSkill101yesterdayMITA162Claude Code, Codex
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playwright-climicrosoft/playwrightSkill100kyesterdayApache-2.0A19Claude Code
browser-automationopenclaw/openclawSkill394ktodayMITA36Claude Code
systematic-debuggingobra/superpowersSkill314k4d agoMITA21Claude Code
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