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 truecourse-ai/truecourse --skill truecourse-analyzegit clone --depth 1 https://github.com/truecourse-ai/truecourseWrote 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/truecourse-ai/truecourse/truecourse-analyze)<a href="https://agentmods.dev/skills/truecourse-ai/truecourse/truecourse-analyze"><img src="https://agentmods.dev/badge/skills/truecourse-ai/truecourse/truecourse-analyze.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 20 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 28 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 29 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 49 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00013 | $0.00818 |
| Opus 5 | $0.00006 | $0.00409 |
| Sonnet 5 | $0.00003 | $0.00164 |
| Haiku 4.5 | $0.00001 | $0.00082 |
Grade A, and why
truecourse-analyze 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.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TrueCourse Analyze
Run architecture analysis on the current repository using TrueCourse.
Important
- Full analysis stashes any uncommitted changes, analyzes the clean working tree, then unstashes. The user's uncommitted work is preserved.
- Diff check analyzes the full working tree (including uncommitted changes — it does NOT stash) and compares the result against the last full analysis baseline. The report lists violations newly introduced and violations resolved since that baseline. Prefer diff for in-progress work where the user is iterating on changes.
- Always invoke via
npx -y— without-y, npx will hang on the "Ok to proceed?" prompt whenever the user hasn't cached the latesttruecourseversion (which happens every time we publish a new release). - LLM rules cost tokens. Never pass
--llmwithout first relaying the token estimate to the user and getting approval. See the LLM flow below.
Instructions
1. Pick mode
Ask the user whether they want a full analysis or a diff check. If they said "diff" in their request, default to diff.
- Full:
npx -y truecourse analyze - Diff:
npx -y truecourse analyze --diff
2. Decide on LLM rules
LLM rules add higher-value insights but cost tokens per run. Ask the user one question: "Run LLM-powered rules this time?" If the user is unsure, offer to run deterministic-only first (no tokens, fast) and add LLM later.
- If user approves LLM: append
--llmto the command. - If user declines LLM or wants a free run: append
--no-llm.
You MUST pass either --llm or --no-llm — running without either in a non-interactive shell will exit with an error naming the flags.
3. Run the command
Use the Bash tool. This is long-running (minutes, especially with --llm) — use a timeout of at least 600000ms (10 minutes).
4. Summarize
When the command finishes, read the printed summary and relay the key numbers:
- Full analyze: one line with the total violation count and per-severity breakdown, e.g.
15 violations (2 critical, 5 high, 8 medium). - Diff analyze:
Changed files: N (X modified, Y new, Z deleted)andSummary: N new issues, N resolved. If you see⚠ Results may be stale — baseline analysis has changed., surface that warning to the user and suggest running a fullnpx -y truecourse analyzeto refresh the baseline. - If the command errored, relay the error message.
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 · 65 lines · 13 tokens per session scan A a889a64027c4
truecourse-analyze is a skill published in the GitHub repository truecourse-ai/truecourse (528 stars, last pushed 2d ago), licensed MIT. It adds 13 tokens to every session and 818 once invoked, about $0.0001 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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