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 jrobelia/inventree-plugin-ai-toolkit --skill teachgit clone --depth 1 https://github.com/jrobelia/inventree-plugin-ai-toolkitWrote 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/jrobelia/inventree-plugin-ai-toolkit/teach)<a href="https://agentmods.dev/skills/jrobelia/inventree-plugin-ai-toolkit/teach"><img src="https://agentmods.dev/badge/skills/jrobelia/inventree-plugin-ai-toolkit/teach/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/jrobelia/inventree-plugin-ai-toolkit/teach"><img src="https://agentmods.dev/badge/skills/jrobelia/inventree-plugin-ai-toolkit/teach.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 | $0.00015 | $0.01944 |
| Opus 5 | $0.00008 | $0.00972 |
| Sonnet 5 | $0.00003 | $0.00389 |
| Haiku 4.5 | $0.00002 | $0.00194 |
Grade A, and why
teach 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 8d 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.
This is a copy
95% identical to teach — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The user has asked you to teach them something. This is a stateful request - they intend to learn the topic over multiple sessions.
Teaching Workspace
Treat the current directory as a teaching workspace. The state of their learning is captured in this directory in several files:
MISSION.md: A document capturing the reason the user is interested in the topic. This should be used to ground all teaching. Use the format in MISSION-FORMAT.md../reference/*.html: A directory of reference materials. These are the compressed learnings from the lessons - cheat sheets, reference algorithms, syntax, yoga poses, glossaries. They are the raw units of learning. They should be beautiful documents which print out well, and are designed for quick reference.RESOURCES.md: A list of resources which can be explored to ground your teaching in contextual knowledge, or to acquire knowledge and wisdom. Use the format in RESOURCES-FORMAT.md../learning-records/*.md: A directory of learning records, which capture what the user has learned. These are loosely equivalent to architectural decision records in software development - they capture non-obvious lessons and key insights that may need to be revised later, or drive future sessions. These should be used to calculate the zone of proximal development. They are titled0001-<dash-case-name>.md, where the number increments each time. Use the format in LEARNING-RECORD-FORMAT.md../lessons/*.html: A directory of lessons. A lesson is a single, self-contained HTML output that teaches one tightly-scoped thing tied to the mission. This is the primary unit of teaching in this workspace../assets/*: Reusable components shared across lessons. See Assets.NOTES.md: A scratchpad for you to jot down user preferences, or working notes.
Philosophy
To learn at a deep level, the user needs three things:
- Knowledge, captured from high-quality, high-trust resources
- Skills, acquired through highly-relevant interactive lessons devised by you, based on the knowledge
- Wisdom, which comes from interacting with other learners and practitioners
What ships with it
5 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.
- 8d ago First seen · 141 lines · 15 tokens per session scan A 6d2dbe5e0308
teach is a skill published in the GitHub repository jrobelia/inventree-plugin-ai-toolkit (1 stars, last pushed 21d ago), licensed MIT. It adds 15 tokens to every session and 1,944 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to teach, differing in 8 lines, and is treated as a copy.
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