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 OutlineDriven/odin-claude-plugin --skill autolearngit clone --depth 1 https://github.com/OutlineDriven/odin-claude-pluginWrote 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/outlinedriven/odin-claude-plugin/autolearn)<a href="https://agentmods.dev/skills/outlinedriven/odin-claude-plugin/autolearn"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/autolearn/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/outlinedriven/odin-claude-plugin/autolearn"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/autolearn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00026 | $0.04333 |
| Opus 5 | $0.00013 | $0.02167 |
| Sonnet 5 | $0.00005 | $0.00867 |
| Haiku 4.5 | $0.00003 | $0.00433 |
Grade A, and why
autolearn 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.
How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autolearn
Contract
| Field | Bound contract |
|---|---|
| Trigger | A non-trivial fix has been verified (observed working, not hoped working), or explicit autolearn or refresh invocation. |
| Authority | Reversible local: writes only the operating repo's docs/solutions/ and repo-root CONCEPTS.md; rollback is version control. No remote mutation. |
| Side effect | Writes or refreshes docs/solutions/ learning docs and CONCEPTS.md; stages only the surfaces this skill wrote or edited. |
| Done | A validated learning or concept entry exists, or an explicit determination that nothing qualifies. |
Inputs
- The verified fix or solved problem, from conversation history or codebase. Must be supplied or derivable from context.
- Optional:
mode:refresh [scope]to maintain existing docs;mode:headlessfor non-interactive operation. - Optional: an injected auto-memory block (supplementary context, not primary evidence).
Procedure
0. Route the mode
Strip mode: tokens from arguments before treating the remainder as context or scope.
- Capture (default): document one solved problem into docs/solutions/.
- Vocabulary capture: a durable, reusable project term surfaces; reconcile CONCEPTS.md.
- Memory handoff: a fact about the user, preferences, or cross-project context surfaces; do not write it into docs/solutions/ or CONCEPTS.md; surface it as a memory-handoff candidate for the memory system to capture.
- Refresh: maintain existing docs/solutions/ and CONCEPTS.md.
- Headless: overlays any mode; skip all questions, never pause, apply safe actions, mark uncertain as stale.
Fire automatically on a trigger phrase ("that worked", "it's fixed", "working now", "problem solved", "verified the fix", "tests pass now", "build succeeds", "that approach failed") or after a verified non-trivial fix. Auto-firing is permission to evaluate, not permission to fabricate.
One run can do all three repo-scoped actions: write a learning doc, reconcile a concept, and flag a memory-handoff candidate.
What ships with it
6 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.
- 2d ago Changed · +64 lines · -39 tokens per session ca2e58b35b18
- 9d ago First seen · 173 lines · 65 tokens per session scan A c7a9e9bf2e16
autolearn is a skill published in the GitHub repository OutlineDriven/odin-claude-plugin (35 stars, last pushed yesterday), licensed Apache-2.0. It adds 26 tokens to every session and 4,333 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 2026-08-30.
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