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/mine-skillsnpx skills add Tarekkharsa/agentstack --skill mine-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/mine-skills)<a href="https://agentmods.dev/skills/tarekkharsa/agentstack/mine-skills"><img src="https://agentmods.dev/badge/skills/tarekkharsa/agentstack/mine-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 | $0.00059 | $0.00818 |
| Opus 5 | $0.00030 | $0.00409 |
| Sonnet 5 | $0.00012 | $0.00164 |
| Haiku 4.5 | $0.00006 | $0.00082 |
Grade A, and why
mine-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 5d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mine skills from your sessions
Use when you want to turn what kept going wrong into skills that stop it going wrong — analyze the last week/month of agent sessions, find the moments worth teaching, and draft skills from them.
A one-off mistake is not a skill. A mistake you corrected twice — or a procedure you re-explained in three different sessions — is the definition of one.
Where the data is
- Claude Code:
~/.claude/projects/<project-hash>/<session-id>.jsonl— one event per line; assistant turns carrymessage.usagetoken counts, tool-use events name the tool/skill invoked, user turns hold corrections. - Codex:
~/.codex/sessions/YYYY/MM/DD/rollout-*.jsonl— lines are{timestamp, type, payload}; payload types includeuser_message,message(roles user/assistant/developer),function_call/function_call_output,token_count,task_started/task_complete.
Both formats are undocumented and drift — tolerate unknown lines, never assume a fixed schema. Use python for the parsing, not shell one-liners.
The loop
- Harvest — walk both transcript trees, scoped by date (e.g. last 30 days). Note which agents you could actually see; coverage is uneven.
- Detect skill-worthy moments (signals below).
- Cluster & rank — group recurrences of the same failure across
sessions; rank by
frequency × wasted tokens. Two strong clusters beat twenty weak ones — propose few, high-signal candidates. - Draft — for each top cluster, write the corrected procedure as a SKILL.md (use the skill-creator skill if available). The skill teaches the right way, not a description of the failure.
- Land it on the rails — show the draft to the user; on approval:
agentstack more lib add ./<draft-dir> --name <name> --write. That path content-scans it, records provenance, checksums it, and makes it referenceable by name from any project (and syncable vialib sync).
Detection signals (strongest first)
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.
- 5d ago First seen · 67 lines · 59 tokens per session scan A 442474393e3d
mine-skills is a skill published in the GitHub repository Tarekkharsa/agentstack (3 stars, last pushed 22d ago), licensed Apache-2.0. It adds 59 tokens to every session and 818 once invoked, about $0.0003 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.
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.
generate-server-card
Generate an MCP server card JSON (mcp-gateway-registry format) by analyzing server source code in a folder or GitHub URL. Studies code to detect server name, tools, transport, auth, and generates a registry-compatible config.