Borrowing it
Nothing to install: this file belongs to 1cFE/fusion-tea. 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/1cFE/fusion-tea/main/.agents/skills/audit-models/SKILL.mdgit clone --depth 1 https://github.com/1cFE/fusion-teaWrote 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/1cfe/fusion-tea/audit-models)<a href="https://agentmods.dev/skills/1cfe/fusion-tea/audit-models"><img src="https://agentmods.dev/badge/skills/1cfe/fusion-tea/audit-models/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/1cfe/fusion-tea/audit-models"><img src="https://agentmods.dev/badge/skills/1cfe/fusion-tea/audit-models.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 | $0.00019 | $0.00979 |
| Opus 5.5 | $0.00008 | $0.00392 |
| Sonnet 5.5 | $0.00004 | $0.00196 |
| Haiku 4.5 | $0.00002 | $0.00098 |
Grade A, and why
audit-models 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 24d 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.
Before executing this skill, read .agentic-mbse/claude.md in Claude Code or .agentic-mbse/codex.md in Codex. Resolve supporting paths from this skill’s installed directory; keep generated outputs in the project or a temporary directory. Read referenced skills from .agents/skills/<name>/SKILL.md when their guidance is needed.
Audit Models
Use the assigned scope and “Review Brief and Context Limits” in modeling_project/MODELING_PROCESS.md. For a focused question, read only the supplied entry sections and primary evidence within the brief’s budget; return missing evidence before expanding. Apply the broader checks below only to claims in scope. Save a short finding in the existing work record or requested evidence path; a separate report is useful for a substantive assessment.
Independently assess whether the model supports its promised outcomes and intended use. Run as a fresh non-author reviewer without inherited author conversation. For a substantive audit, save work/analysis/YYYYMMDD-HHMMSS_audit_{scope}.md and link it from the work item or epic.
Choose the Scope
- Work item audit: verify the spec outcomes, changed behavior, and affected dependencies/consumers. Read the plan's evidence and relevant design sections; expand where a finding requires it.
- Epic audit: verify epic success criteria, item audit evidence, dependency handoffs, and cross-item integration. Positive item audits do not establish the integrated outcome by themselves.
- Project audit: assess the requested broader system claims against project requirements, source evidence, and actual model coverage.
Use the already authorized scope or clarify what is to be assessed. State the examined revision, supported use, and evidence limits. A narrow audit must not read as certification of every parameter or engineering assumption.
Verify the Outcome
Read the four-view completion obligation and relevant architecture/pattern rules in modeling_project/MODELING_PROCESS.md, the applicable requirements and architectural decisions, and the implementation. Check the physical and behavioral relationships behind the calculations where they matter to the claim. Trace the affected claim through requirements, behavior, component occurrences/interfaces, analytical bindings, and verification evidence. Component ownership, interfaces, analytical bindings, and consumer interpretation must agree. Check that documented approximations still support the claim; an inventory of declarations does not establish this. When calculation wiring changes, inspect which occurrence each input resolves to and check that relevant public-input changes reach its consumers.
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.
- 24d ago Changed · -7 lines 8df15b2b2b73
- 1mo ago First seen · 53 lines · 19 tokens per session scan A 5451715254ce
audit-models is a skill published in the GitHub repository 1cFE/fusion-tea (5 stars, last pushed 24d ago), licensed MIT. It adds 19 tokens to every session and 979 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 2026-09-29.
audit-models compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| audit-models1cFE/fusion-tea | Skill | 5 | 24d ago | MIT | A | 19 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |