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 commands/codeready-toolchain/tarsy/learngit clone --depth 1 https://github.com/codeready-toolchain/tarsyWhat 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 | $0.00015 | $0.00146 |
| Opus 5 | $0.00008 | $0.00073 |
| Sonnet 5 | $0.00003 | $0.00029 |
| Haiku 4.5 | $0.00002 | $0.00015 |
Grade A, and why
learn 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 2d 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.
What it actually says
Analyze this session and extract non-obvious learnings into AGENTS.md files.
AGENTS.md can exist at any directory level. Prefer the nearest package/feature directory over the repo root.
Include only:
- Hidden relationships between modules
- Surprising execution paths
- Non-obvious env/config
- Debugging breakthroughs
- Build/test commands missing from docs
- Files that must change together
Do not include obvious docs facts, standard language behavior, or session chatter.
Process: review session → choose scope → read existing AGENTS.md → append 1–3 line bullets → summarize what changed.
$ARGUMENTS
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.
- 2d ago First seen · 23 lines · 15 tokens per session scan A 0b1fbb61853e
learn is a command published in the GitHub repository codeready-toolchain/tarsy (10 stars, last pushed 2d ago), licensed Apache-2.0. It adds 15 tokens to every session and 146 once invoked, about $0.0001 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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fix-issue
!gh issue view $ARGUMENTS 2>/dev/null || echo "Could not fetch issue $ARGUMENTS".