agentmods.dev

asset-identify

asset-identify is a skill for Claude Code, Codex from microsoft/cat-agent-skills. It costs 151 tokens per session (1,488 once invoked), scanned A, original, MIT.

A tool that scores possible reusable assets and checks whether a final-deliverable package is complete. An asset is a piece of work or information that may be useful again.

In plain words
What is it for?
Use it to shortlist reusable assets, find missing closeout materials, and assess each candidate against a reuse rubric.
Why use it?
It helps distinguish useful reusable material from incomplete or unsuitable candidates after closeout sources have been assembled.

Skill for Claude CodeCodex ✓ vendor

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

not rated 101repo +5 yesterday A scan 151 tokens original MIT

Good fit Use it to shortlist reusable assets, find missing closeout materials, and assess each candidate against a reuse rubric.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/microsoft/cat-agent-skills/asset-identify
View source ↗ microsoft/cat-agent-skills
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 asset-identify
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 asset-identify

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/asset-identify"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/asset-identify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 151 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,488 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 $0.00151 $0.01488
Opus 5.5 $0.00060 $0.00595
Sonnet 5.5 $0.00030 $0.00298
Haiku 4.5 $0.00015 $0.00149

Measured yesterday against content hash 7ca3ad1909f9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

asset-identify 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 3 executable files (scripts/asset_identify.py, scripts/closeout_core.py, scripts/steering_guard.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-closeout-knowledge-harvest/skills/asset-identify/SKILL.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Asset Identify

Purpose

Apply references/reuse-asset-rubric.md deterministically: final deliverable index, closeout completeness gaps, reuse score and reuse recommendation for each candidate asset.

When to use

After artifact-assemble in every closeout harvest and whenever a delivery lead asks "what can we reuse from this?" or "is the closeout package complete?".

When NOT to Use

  • Raw engagement sources have not been assembled into the contract - use artifact-assemble.
  • The user asks what the team learned or how evidence should be grouped - use lesson-cluster.
  • The user asks whether an item is safe to share, release or reuse - use sanitize-check.
  • The user asks for a knowledge-record or case-study handoff draft - use knowledge-record.

Inputs

The contract entry payload (ps.engagement-closeout-knowledge-harvest.v1) containing artifacts and candidate_assets.

Steps

  1. Run scripts/asset_identify.py --input engagement.json --out asset_shortlist.json (add --generated-at <ISO-8601 UTC> only if run_metadata.generated_at is absent). The engine validates the input, then screens every free-text field for embedded instructions before scoring.
  2. Quote the engine's deliverable gaps, reuse scores and any screening_holds (hold ID, path, reason) verbatim.
  3. Pass all confidentiality markers and aggregation tokens forward unchanged to lesson-cluster and sanitize-check.
  4. Make clear that a high reuse score is not a clearance decision.
  5. If the engine exits non-zero (exit 2 prints asset_identify: input error: ...; nothing written), stop and report the error; never estimate a score. An input above the screening ceiling (1000 records per array or escalations list, 2500 across the arrays and escalations together, 200 items per named_people or third_party_products list) is refused this way; ask for one workstream or phase per run rather than dropping records.

Tools

Run scripts/asset_identify.py with the shell tool and read its JSON output with the file-read tool. No connector writes or outbound actions.

Read the full file on GitHub · 73 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 73 lines · 151 tokens per session scan A 7ca3ad1909f9

Subscribe to this mod's changes

asset-identify is a skill published in the GitHub repository microsoft/cat-agent-skills (101 stars, last pushed yesterday), licensed MIT. It adds 151 tokens to every session and 1,488 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.

Project managementResearch
Related

asset-identify compared with skills from other repositories

asset-identify next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
asset-identifymicrosoft/cat-agent-skillsSkill101yesterdayMITA151Claude Code, Codex
imagegenopenai/codexSkill134ktodayApache-2.0A113Codex
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79kyesterdayMITA200Claude Code, Codex
playwright-climicrosoft/playwrightSkill100kyesterdayApache-2.0A19Claude Code
browser-automationopenclaw/openclawSkill394ktodayMITA36Claude Code
systematic-debuggingobra/superpowersSkill314k4d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143ktodayMITA95Claude Code