Borrowing it
Nothing to install: this file belongs to tjmustard/Hypergraph-Coding-Agent-Framework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tjmustard/Hypergraph-Coding-Agent-Framework/main/.agents/skills/hyper-tutorial-audit/SKILL.mdgit clone --depth 1 https://github.com/tjmustard/Hypergraph-Coding-Agent-FrameworkWrote 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/tjmustard/hypergraph-coding-agent-framework/hyper-tutorial-audit)<a href="https://agentmods.dev/skills/tjmustard/hypergraph-coding-agent-framework/hyper-tutorial-audit"><img src="https://agentmods.dev/badge/skills/tjmustard/hypergraph-coding-agent-framework/hyper-tutorial-audit/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/tjmustard/hypergraph-coding-agent-framework/hyper-tutorial-audit"><img src="https://agentmods.dev/badge/skills/tjmustard/hypergraph-coding-agent-framework/hyper-tutorial-audit.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 | $0.00063 | $0.01619 |
| Opus 5.5 | $0.00025 | $0.00648 |
| Sonnet 5.5 | $0.00013 | $0.00324 |
| Haiku 4.5 | $0.00006 | $0.00162 |
Grade A, and why
hyper-tutorial-audit 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 2mo 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tutorial Audit
This skill is designed to run after /hyper-tutorial-run in the same conversation. It reads the tutorial, reviews what failed during the walk-through, interviews the user about their goal and constraints, and generates a structured goal prompt that can be pasted at the start of a fresh Claude Code session to drive an automated fix loop.
Do not re-run tutorial commands. This skill is read-only and interview-driven. The fix work happens in the new session the goal prompt creates.
Step 1 — Locate Tutorial
- If an argument was passed (tutorial name or path), resolve
tutorials/<name>/tutorial.md. - Otherwise, scan the current conversation for mentions of a tutorial name or path from a recent
/hyper-tutorial-runsession and use that. - If still ambiguous, list all
tutorials/*/tutorial.mdfiles found in the project. Use AskUserQuestion to let the user select one.
Step 2 — Read Tutorial
Read the full tutorial.md. Extract and hold in memory:
- Title (from the
#heading) - Overview / learning objective (the first paragraph or
## Overviewsection) - All section headings (
##) with their ordinal numbers - Any prerequisite declarations (package names, versions, tools)
Step 3 — Review Conversation Context
Scan the current conversation (everything visible, not just recent messages) for evidence from the /hyper-tutorial-run session:
- Which sections the user reached or attempted
- Error messages, stack traces, or failure descriptions that appeared in chat
- Steps the user skipped, flagged as broken, or noted needed help
Build an internal summary of failures — do not ask the user to re-describe or re-paste anything already visible in context.
Step 4 — Interview: Goal (HITL Gate #1)
Use AskUserQuestion with at most 2 questions:
Question 1 — What are you trying to accomplish? (multi-select)
- Learn the concept the tutorial teaches
- Get the feature working in my project
- Use as reference for a future task
- Reproduce a bug or a demo
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.
- 2mo ago First seen · 166 lines · 63 tokens per session scan A 874fa840ce52
hyper-tutorial-audit is a skill published in the GitHub repository tjmustard/Hypergraph-Coding-Agent-Framework (2 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 1,619 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.
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