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 Tyler-R-Kendrick/agent-skills --skill learngit clone --depth 1 https://github.com/Tyler-R-Kendrick/agent-skillsWrote 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/tyler-r-kendrick/agent-skills/learn)<a href="https://agentmods.dev/skills/tyler-r-kendrick/agent-skills/learn"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/learn/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/tyler-r-kendrick/agent-skills/learn"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/learn.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 | $0.00105 | $0.00604 |
| Opus 5 | $0.00053 | $0.00302 |
| Sonnet 5 | $0.00021 | $0.00121 |
| Haiku 4.5 | $0.00011 | $0.00060 |
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 11d 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learn
Use this skill to turn a user correction into a generalized steering rule. Keep STEERING.md as an index, and keep details in linked RDF/Turtle files under ~/.agents/.steering/.
This turns feedback loops into explicit, inspectable learnings. See correction-to-learning.md for the correction-to-learning model.
Route
- IF the user corrects an agent response, read correction-to-learning.md and zpd-teaching-loop.md.
- IF creating or updating steering artifacts, read steering-index-contract.md and rdf-contract.md.
- IF using the deterministic helper, read cli-usage.md and run
node skills/ai/learn/scripts/dist/learn.js. - ELSE answer normally and do not create steering entries.
Core Workflow
- Identify the correction, the agent behavior it changes, and the broader class of future tasks it should affect.
- Generalize the correction into a strategy or preference, not a one-off fact.
- If memory is available, search for related prior corrections and add
memory://evidence links; keep facts in memory, not in steering. - Add evidence links to docs, instruction files, conversations, or other sources.
- Use the CLI to write the RDF entry and regenerate
STEERING.md. - Briefly teach the agent what reasoning move to practice next time.
Best Practices
- Always store durable learnings as generalized strategies or preferences, not isolated task facts.
- Keep
STEERING.mdas a conditional index and load linked RDF files only when the current task matches the entry. - Require evidence links for every learning so agents can inspect provenance before relying on the rule.
- Use the zone of proximal development to explain the next reasoning move the correction teaches.
- Prefer deterministic CLI writes over manual steering edits to avoid broken links, duplicate IDs, or stale index rows.
What ships with it
20 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.
- AGENTS.md 2.0 KB
- metadata.json 480 B
- README.md 683 B
- references/cli-usage.md 1.4 KB
- references/correction-to-learning.md 1.6 KB
- references/rdf-contract.md 1.9 KB
- references/steering-index-contract.md 1.7 KB
- references/zpd-teaching-loop.md 1.4 KB
- rules/_sections.md 1.1 KB
- rules/_template.md 364 B
- rules/learn-always-store-durable-learnings-as-generalized-strategies-or.md 432 B
- rules/learn-keep-steering.md 334 B
- rules/learn-prefer-deterministic-cli-writes-over-manual-steering-edits.md 455 B
- rules/learn-require-evidence-links-for-every-learning-so-agents-can.md 434 B
- rules/learn-use-the-zone-of-proximal-development-to-explain-the-next.md 406 B
- scripts/dist/learn.js 19 KB runs code
- scripts/fixtures/sample-learning.json 768 B
- scripts/src/learn.ts 18 KB runs code
- scripts/test/learn.test.js 14 KB runs code
- scripts/tsconfig.json 330 B
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.
- 11d ago First seen · 48 lines · 105 tokens per session scan A 4da239c71649
learn is a skill published in the GitHub repository Tyler-R-Kendrick/agent-skills (11 stars, last pushed 3mo ago), licensed MIT. It adds 105 tokens to every session and 604 once invoked, about $0.0005 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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