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.
npx agentmods add skills/tarekkharsa/agentstack/finding-skillsnpx skills add Tarekkharsa/agentstack --skill finding-skillsgit clone --depth 1 https://github.com/Tarekkharsa/agentstackWrote 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/tarekkharsa/agentstack/finding-skills)<a href="https://agentmods.dev/skills/tarekkharsa/agentstack/finding-skills"><img src="https://agentmods.dev/badge/skills/tarekkharsa/agentstack/finding-skills.svg" alt="Measured on agentmods" 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 | $0.00078 | $0.00718 |
| Opus 5 | $0.00039 | $0.00359 |
| Sonnet 5 | $0.00016 | $0.00144 |
| Haiku 4.5 | $0.00008 | $0.00072 |
Grade A, and why
finding-skills 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 3d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Finding skills
Use this skill when the user is looking for a capability that might exist as an installable skill — "how do I work with PDFs here", "find a skill for code review", "add the pdf skill from anthropics/skills" — or when you wish you had domain instructions you don't have.
Where skills come from
agentstack search <query>— the user's central library, the embedded catalog, and the official MCP Registry, in one pass. Results marked(in manifest)are already installed.- Any skills repo on GitHub/GitLab — the ecosystem publishes SKILL.md
directories, and
agentstack add skillspeaks its conventions:
agentstack add skill anthropics/skills --list # inspect a repo's skills
agentstack add skill anthropics/skills --skill pdf # preview one (dry run)
agentstack add skill owner/repo@pdf # same, alias spelling
agentstack add skill https://github.com/o/r/tree/main/skills/pdf
agentstack add skill ./local-skill
agentstack more lib add owner/repo --skill pdf # into the central library
Everything previews first. The dry run fetches into transient staging,
scans the content, and shows the manifest diff plus the exact digest that
would be pinned — nothing persistent changes until a human re-runs with
--write.
Judge quality by evidence, not popularity
There are no install counts here, on purpose. The signals that matter:
- Scan verdict — the preview shows per-skill findings. High-severity findings (hidden Unicode) block the add; warnings deserve a read before you recommend proceeding.
- Pin + provenance — after a write, the lockfile pins the exact commit
and content checksum, and
agentstack more explain <name>shows where a skill came from and whether its content still matches its pin. - Description quality — a skill without a frontmatter description is invisible to search and to agents; treat that as a smell.
Rules for agents
- Propose, don't apply: run the dry run, show the user the preview, and let
them re-run with
--write. Never pass--allow-flaggedyourself — a blocked scan finding is the user's decision. - Prefer the central library for skills the user will want across repos
(
agentstack more lib add …, then reference by name in profiles); prefer the project manifest for repo-specific skills. - After a write in a gateway-served (zero-files) project, remind the user
that trust re-gates on the edit: they run
agentstack trust .themselves — never run it for them. - When nothing suitable exists, say so and offer to help directly; a new
skill directory with a
SKILL.md(name + description frontmatter) is all it takes to make the solution reusable.
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.
- 3d ago First seen · 62 lines · 78 tokens per session scan A 8651e5852538
finding-skills is a skill published in the GitHub repository Tarekkharsa/agentstack (3 stars, last pushed 20d ago), licensed Apache-2.0. It adds 78 tokens to every session and 718 once invoked, about $0.0004 per session on Opus 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-frontend-check
Smoke-test or verify UI behaviour on the local Jarvis Registry frontend running at http://localhost/gateway. Use for manual regression checks, bug-fix verification, and end-to-end confirmation of specific flows without running the automated test suite.
release-notes
Edit an existing GitHub release's body into the project's bilingual (English + Chinese) template format with a References section built from merged PRs. Use when 修改 release、整理发布说明、release notes、编辑 release 内容、发版后整理、edit release body.
release-notes
Create release notes for a new version tag. Gathers all commits, PRs, issues fixed, and breaking changes since a previous release. Creates the release notes markdown file, tags the repo, and pushes. Asks the user to confirm the base version to diff against.
create-milestone
Create a GitHub milestone for an upcoming release. Suggests the next version based on the latest release, gathers all merged PRs and closed issues since that release, presents a draft with two tables (Issues and PRs) for user approval, then creates the milestone and assigns all approved items.
pr-review
Review a GitHub pull request using multiple expert personas. Takes a PR URL as input, analyzes the changes, and generates comprehensive review feedback from different perspectives (Merge Specialist, Frontend, Backend, Security, DevOps, AI/Agent, SRE, Chief Architect).
generate-agent-card
Generate an A2A agent card JSON by analyzing agent source code in a folder or GitHub URL. Studies the code to detect agent name, skills, tools, auth, protocol, and generates a spec-compliant agent card.