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 craigcossairt/trellis --skill learngit clone --depth 1 https://github.com/craigcossairt/trellisWrote 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/craigcossairt/trellis/learn)<a href="https://agentmods.dev/skills/craigcossairt/trellis/learn"><img src="https://agentmods.dev/badge/skills/craigcossairt/trellis/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/craigcossairt/trellis/learn"><img src="https://agentmods.dev/badge/skills/craigcossairt/trellis/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 | $0.00077 | $0.00106 |
| Opus 5.5 | $0.00031 | $0.00042 |
| Sonnet 5.5 | $0.00015 | $0.00021 |
| Haiku 4.5 | $0.00008 | $0.00011 |
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 20d 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
Read and follow .claude/skills/learn/SKILL.md. Resolve repository paths from the Git root.
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.
- 20d ago Changed · -104 lines d14207ed5e8a
- 25d ago Changed · +38 lines · +19 tokens per session 3500f71a27ef
- 1mo ago First seen · 73 lines · 58 tokens per session scan A 5f7667190c8b
learn is a skill published in the GitHub repository craigcossairt/trellis (5 stars, last pushed 13d ago), licensed MIT. It adds 77 tokens to every session and 106 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
lov-auto-context
Manual or hook-triggered context operator. Evaluates the current session for pollution (long conversations, topic drift, stale noise), AND takes concrete context-shaping actions: writing project memory, updating global or project CLAUDE.md (with diff + confirm), and recommending harness commands like /fork, /compact…
lov-ataru-indexing
A maintenance tool for building, repairing, or checking a local searchable index of Ataru AI conversation history. An index is an organised lookup structure that makes searching stored records faster.
lov-search-chat
A local search tool for recalling relevant parts of earlier AI conversations from an indexed memory store. It returns matching sessions and identifiable excerpts from the original conversations.
lov-memory-add
A knowledge-capture workflow that saves user-selected information as a categorized, tagged note with its source and an index entry. It stores the note as Markdown and can read existing records to avoid duplicates or conflicts.
lov-memory-search
A search workflow for a configured personal knowledge base, including memory and distill folders. It searches indexes and, when needed, note text, then returns matching titles, excerpts, dates, sources, and real file links.
continual-learning
Orchestrate continual learning by delegating transcript mining to agents-memory-updater and writing durable memory to local JSON (never root AGENTS.md Learned sections). USE WHEN continual learning, mine prior chats, maintain agent memory, or the stop hook triggers this skill.