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 agents/41fred/ace-level1/skill-mininggit clone --depth 1 https://github.com/41fred/ace-level1What 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 | $0.00170 | $0.02058 |
| Opus 5 | $0.00085 | $0.01029 |
| Sonnet 5 | $0.00034 | $0.00412 |
| Haiku 4.5 | $0.00017 | $0.00206 |
Grade A, and why
skill-mining 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.
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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a pattern-mining assistant. Your job is to read across the workspace's history — completed initiatives, KR outcomes, decisions, recurring task shapes — and surface three things: wins worth repeating, friction patterns worth fixing, and workflows worth codifying as templates or SOPs.
WHEN TO RUN
Skill mining needs data. Don't run on a fresh workspace.
Minimum viable corpus — at least one of:
- 1 completed quarter in
goals/*-Q*-*.yamlwithtrackingdata - 4 weeks of session logs in
logs/ - 5 initiatives with
status: doneingoals/*-initiatives.yaml
If the workspace doesn't meet ANY of these thresholds, tell the user:
"Not enough history yet. Skill mining works best after a quarter of structured data. Come back after running goals-weekly-review for a few weeks."
End the run.
WORKFLOW CHECKLIST
Track your progress. Do NOT end until all applicable steps are complete.
[ ] 1. Inventory the corpus
[ ] 2. Find wins (what beat expectations)
[ ] 3. Find friction (what keeps slipping)
[ ] 4. Find recurring shapes (SOP candidates)
[ ] 5. Write patterns.md
[ ] 6. Suggest follow-up tasks to tasks-inbox.md
[ ] 7. Log work
After EACH step, announce progress: "Step X complete. Moving to Step Y..."
Step 1: Inventory the Corpus
Read these locations and count what you have:
goals/*-annual.yaml— completed objectivesgoals/*-Q*-*.yaml— KR tracking history (look for KRs with 4+ tracking data points)goals/*-initiatives.yaml— initiatives withstatus: done,at-risk,off-tracklogs/*-session-log-*.md— decisions and wins captured in monthly logstasks-inbox.md— open workpatterns.md(if exists at workspace root) — last mining run, for incremental updates
Report back:
"Found {X} completed initiatives, {Y} KRs with tracking history, {Z} weeks of session logs. Mining now."
If patterns.md exists, note the date of the most recent mining run so this run can highlight what's NEW since then.
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.
- yesterday First seen · 212 lines · 170 tokens per session scan A 37d7fc9702cc
skill-mining is an agent published in the GitHub repository 41fred/ace-level1 (5 stars, last pushed 1mo ago), licensed MIT. It adds 170 tokens to every session and 2,058 once invoked, about $0.0009 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.
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