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 skills add hqhq1025/skill-optimizer --skill skill-minergit clone --depth 1 https://github.com/hqhq1025/skill-optimizerWrote 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/hqhq1025/skill-optimizer/skill-miner)<a href="https://agentmods.dev/skills/hqhq1025/skill-optimizer/skill-miner"><img src="https://agentmods.dev/badge/skills/hqhq1025/skill-optimizer/skill-miner/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/hqhq1025/skill-optimizer/skill-miner"><img src="https://agentmods.dev/badge/skills/hqhq1025/skill-optimizer/skill-miner.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 | $0.00032 | $0.00559 |
| Opus 5 | $0.00016 | $0.00280 |
| Sonnet 5 | $0.00006 | $0.00112 |
| Haiku 4.5 | $0.00003 | $0.00056 |
Grade A, and why
skill-miner 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 9d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Miner
Overview
Mine real agent usage for new skill opportunities. The goal is to find repeated workflows, extract the reusable technique, and turn strong candidates into draft skills with evidence.
When To Use
- A user wants to scan past coding-agent sessions for repeated workflows.
- The user suspects they keep asking agents to do similar tasks manually.
- A team wants a backlog of candidate skills based on actual work rather than brainstorming.
- Existing memories, session logs, or project notes contain recurring procedures that have not been packaged.
Do not use to tune an existing skill; use skill-personalizer. Do not use to publish a private skill publicly; use skill-generalizer.
Workflow
- Locate real evidence: session JSONL, memory summaries, repo notes, repeated scripts, and recent project folders.
- Run
scripts/scan_sessions.pyfor a first-pass sanitized cluster report when local session files or exported transcripts are available. - Cluster repeated work by intent, trigger phrasing, tools used, files touched, and verification pattern.
- Filter out one-off tasks, ordinary coding knowledge, and project-specific instructions better suited for
AGENTS.md. - Score candidates by recurrence, friction, risk, portability, and future value.
- For each strong candidate, draft a concise skill name, trigger description, workflow outline, bundled-resource needs, and validation prompts.
- Recommend whether each candidate should stay personal, become a public skill via
skill-generalizer, or be skipped. - If the user asks to proceed, create the selected skill folders and verify frontmatter/layout.
Evidence Rules
- Quote or summarize enough source evidence to justify each candidate.
- Do not expose sensitive transcript content unless the user explicitly asks for raw evidence.
- Avoid turning every repeated task into a skill; prefer workflows where guidance changes future behavior.
- Treat broad intent clusters as navigation hints, not skill drafts.
- Check sampled positives and near misses before trusting a regex-based workflow candidate.
- If session access is incomplete, label findings as partial and list what was scanned.
What ships with it
4 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.
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.
- 9d ago First seen · 46 lines · 32 tokens per session scan A 6aec3459dffc
skill-miner is a skill published in the GitHub repository hqhq1025/skill-optimizer (167 stars, last pushed 3mo ago), licensed MIT. It adds 32 tokens to every session and 559 once invoked, about $0.0002 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 2026-08-30.
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