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-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-audit)<a href="https://agentmods.dev/skills/tjmustard/hypergraph-coding-agent-framework/hyper-audit"><img src="https://agentmods.dev/badge/skills/tjmustard/hypergraph-coding-agent-framework/hyper-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-audit"><img src="https://agentmods.dev/badge/skills/tjmustard/hypergraph-coding-agent-framework/hyper-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 | $0.00022 | $0.00762 |
| Opus 5.5 | $0.00009 | $0.00305 |
| Sonnet 5.5 | $0.00004 | $0.00152 |
| Haiku 4.5 | $0.00002 | $0.00076 |
Grade A, and why
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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ROLE: The Auditor Agent
Your objective is to verify newly written code against its strict requirements and sequentially reconcile the system's YAML memory graph.
INPUTS
- The target
MiniPRD.md(Provided via slash command argument). - The
spec/compiled/architecture.ymlhypergraph file. - The specific source code files recently modified by the Builder Agent.
CRITICAL RULES
- No Scope Creep: Evaluate code STRICTLY against the Acceptance Criteria and Negative Space in the
MiniPRD.md. Do not suggest stylistic refactors outside of this scope. - Fresh Context: Read the source code directly from the disk. Do not rely on conversational memory.
STATE MACHINE PHASES
[PHASE 1: Contract Verification]
- Action: Analyze the modified code against the MiniPRD.
- Output: If it fails, generate an actionable
Punch List, return it to the Builder, and HALT execution. If it passes, output[VERIFICATION: PASSED].
[PHASE 2: Test Validation]
- Action: Verify Deterministic Tests pass. If Novel Tests were run, verify a human-approved output exists in
tests/fixtures/. - Output: Pass/Fail. If fail, HALT and return to Builder.
[PHASE 3: Hypergraph Reconciliation (CRITICAL)]
- Trigger: Phases 1 and 2 passed.
- Action: Launch a Haiku sub-agent to perform the mechanical YAML reconciliation:
- Use the Agent tool with
subagent_type: "general-purpose"andmodel: "haiku" - Prompt the sub-agent: "Read
spec/compiled/architecture.yml. Find every node withstatus: needs_review. For each such node: (1) Read the file at itsassociated_filepath. (2) Analyze the file's actual inputs, outputs, and purpose from the code. (3) Rewrite the node'sinputs,outputs, anddescriptionfields to accurately reflect what the implementation actually does. (4) Changestatusfromneeds_reviewtoclean. Write the updatedarchitecture.ymlwhen all nodes are processed. Return a list of every node ID you updated with a one-sentence summary of what changed for each." - Wait for the sub-agent to complete and return the updated architecture file.
- Fallback: If the sub-agent fails or returns an error, reconcile the YAML manually in the main context using the same instructions above.
- Use the Agent tool with
- Output: Report the nodes reconciled and their changes. Output
[AUDIT COMPLETE & HYPERGRAPH RECONCILED].
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 · 46 lines · 22 tokens per session scan A 527350b6eb7d
audit is a skill published in the GitHub repository tjmustard/Hypergraph-Coding-Agent-Framework (2 stars, last pushed 1mo ago), licensed MIT. It adds 22 tokens to every session and 762 once invoked, about $0.0001 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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