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 ondrej-svec/heart-of-gold-toolkit --skill teachgit clone --depth 1 https://github.com/ondrej-svec/heart-of-gold-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/ondrej-svec/heart-of-gold-toolkit/teach)<a href="https://agentmods.dev/skills/ondrej-svec/heart-of-gold-toolkit/teach"><img src="https://agentmods.dev/badge/skills/ondrej-svec/heart-of-gold-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/ondrej-svec/heart-of-gold-toolkit/teach"><img src="https://agentmods.dev/badge/skills/ondrej-svec/heart-of-gold-toolkit/teach.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 | $0.00069 | $0.01586 |
| Opus 5 | $0.00034 | $0.00793 |
| Sonnet 5 | $0.00014 | $0.00317 |
| Haiku 4.5 | $0.00007 | $0.00159 |
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 12d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Teach (capture a footgun as a proposed trigger)
A guided wrapper around quellis teach. The CLI exists; this skill exists because most users won't drop to a terminal mid-session to write a TOML trigger by hand. Walks the user through naming the finding, runs the CLI, shows the proposed pack entry, and stops — activation is a deliberate second step.
Boundaries
This skill MAY: ask the user to describe the finding, run quellis teach --finding "<text>", read the proposed trigger output, write a one-line summary to the conversation.
This skill MAY NOT: auto-activate the proposed trigger (the CLI's --dry-run-and-review contract is the whole point), edit existing triggers, run other quellis subcommands without explicit user approval, write to the live pack outside of what quellis teach writes.
Teach never auto-promotes. The §2.D acceptance-log substrate exists so triggers earn promotion through observed use; bypassing that throws away the compounding loop.
Common Rationalizations
| Shortcut | Why it fails | The cost |
|---|---|---|
| "Skip the dry-run; just write the trigger directly" | The CLI's classification step produces canonical DON'T/TRIGGER/VERIFICATION/ORIGIN form. Hand-rolled triggers drift from that form and don't compound cleanly into V1.2 personalization. | Pack inconsistency; harder to review patterns later. |
| "Activate immediately because the user said yes" | "Activate immediately" is what §2.D told us doesn't work — the calibration step matters. Proposed triggers sit until the user reviews the pack. | Trigger fatigue from over-eager additions. |
| "Capture every annoying thing as a trigger" | Triggers are for footguns, not preferences. A finding worth a trigger involves real risk — security, destructive, integrity. | Pack noise; real triggers lose signal. |
| "Skip the why — just record the don't" | The CLI writes ORIGIN: <why> for a reason. The why is what calibrates later — was this an incident, a near-miss, a hunch? |
Future-you can't tell if a trigger still earns its keep. |
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.
- 12d ago First seen · 138 lines · 69 tokens per session scan A c74b67d43279
teach is a skill published in the GitHub repository ondrej-svec/heart-of-gold-toolkit (19 stars, last pushed 22d ago), licensed MIT. It adds 69 tokens to every session and 1,586 once invoked, about $0.0003 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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