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 wrg32786/aigent-os --skill learngit clone --depth 1 https://github.com/wrg32786/aigent-osWrote 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/wrg32786/aigent-os/learn)<a href="https://agentmods.dev/skills/wrg32786/aigent-os/learn"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/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/wrg32786/aigent-os/learn"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/learn.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 | $0.00073 | $0.01175 |
| Opus 5.5 | $0.00029 | $0.00470 |
| Sonnet 5.5 | $0.00015 | $0.00235 |
| Haiku 4.5 | $0.00007 | $0.00118 |
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 1mo 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learn
The learning compounding skill. Most principals lose the value of a learning sweep within 48 hours — they read three repos, watch one talk, evaluate two tools, and a week later can't remember what they decided about any of them. /learn captures the structured outcome of every such sweep.
When to use
- The principal has just read a repo, paper, talk, or tool description
- The principal is evaluating something but doesn't have an immediate need
- The principal asks "should I be using X?" or "what did we decide about Y?"
- After any session where the input was learning, not doing
- Triggered by Caddy on prompts like: "/learn", "I just read", "evaluating", "looked into", "should I use", "what did we decide about", "captured this", "interesting tool", "considered tool"
How to execute
Step 1 — Take the input
The principal provides:
- Subject: the thing being evaluated (tool, technique, concept, repo, paper, idea)
- Source: where it came from (URL, talk title, conversation, repo name)
- Snapshot: 2-5 sentences on what the thing is and what it claims to do
If any field is missing, ask one focused question to get it.
Step 2 — Locate it on the modern AI stack
Reference [[Modern AI Infrastructure Stack]]. Place the subject at the right layer:
- Application
- Persistence
- Messaging
- Isolation
- Compute
- Observability
- Orchestration
If it doesn't fit cleanly on the stack, it's either a doctrine concept (note that explicitly) or an artifact-of-AI-trends category (e.g., "agent framework", "prompt-engineering pattern").
Step 3 — Assess relevance
Three categories:
- ADOPT — fits an actual current bottleneck. Action follows.
- HOLD — could fit in a future state, but no current bottleneck. Capture the trigger condition.
- REJECT — wrong category, wrong scale, or violates a load-bearing constraint. Capture the reasoning.
- MONITOR — interesting but no clear path. Re-evaluate next quarter.
Step 4 — Capture reconsideration triggers (for HOLD only)
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.
- 1mo ago First seen · 128 lines · 73 tokens per session scan A 8a41d07392be
Learn is a skill published in the GitHub repository wrg32786/aigent-os (23 stars, last pushed today), licensed MIT. It adds 73 tokens to every session and 1,175 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 2026-09-01.
Other skills, from other repositories
graphify
Use when the user invokes /graphify or asks to build, update, or query a knowledge graph from a folder of files (code, docs, papers, notes, images). Triggers: 'map this codebase', 'graph my notes', 'what is connected across these files', 'community detection', 'GraphRAG', incremental graph update, Neo4j/SVG/GraphML…
insights
Use when the user types /weekly or /monthly, asks for a weekly or monthly journal review or retrospective, asks 'how was my week' or 'how was my month', or wants trends, anomalies, or patterns across recent journal entries. Also fires when regenerating an insight report for a past week or month. NOT for writing…
setup-brain
Set up or upgrade an AI-powered Obsidian vault. Interviews you, builds your vault structure (or works with what you already have), creates your CLAUDE.md memory file, installs tools, and gets you journaling — all in one conversation. Also has a repair/upgrade path for existing users.
second-brain-mapping
Use when the user wants to map or remap their second brain, refresh the vault's queryable metadata index, extract structured frontmatter from typed notes (books, meetings, people, journals, goals), fill wikilink gaps, or surface cross-type insights and patterns no single file shows. Triggers: /second-brain-mapping…
sunday-review
Use when the user asks for the weekly meta-review or Sunday wrap-up of their week and vault: says /sunday, /sunday-review, 'let's do the weekly review,' 'Sunday review,' 'review my week,' 'weekly retro,' 'week in review,' 'end-of-week review,' or wants journals, patterns, vault health, and stale decisions reviewed…
coach
Use when the user says /coach (today, week, month, profile, log), asks what to do today for training, asks for a workout, weekly training plan, or longevity plan, wants to log a finished workout or check lift progression (PR, plateau, deload), or a scheduled morning task fires to drop today's workout into the…