eval-audit

eval-audit is a skill for Claude Code from Goodeye-Labs/truesight-mcp-skills. It costs 40 tokens per session (585 once invoked), scanned A, original, MIT.

A skill for auditing an existing workflow used to evaluate AI systems and reporting findings by severity.

In plain words
What is it for?
Use it to inspect evaluation data, runs, results, review queues, criteria, and deployment practices, then produce findings and next actions.
Why use it?
It helps identify weaknesses in evaluation coverage, error analysis, review practices, and the process for promoting changes.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: names the AskUserQuestion tool.

Part of the truesight plugin — 9 skills, 1 MCP server shipped together

Good fit Use it to inspect evaluation data, runs, results, review queues, criteria, and deployment practices, then produce findings and next actions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/goodeye-labs/truesight-mcp-skills/eval-audit
Install

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.

Any agent
npx skills add Goodeye-Labs/truesight-mcp-skills --skill eval-audit
Clone the repo
git clone --depth 1 https://github.com/Goodeye-Labs/truesight-mcp-skills

Made for: Claude Code.

Or install truesight, the plugin that ships this one along with the rest of its 9 skills, 1 MCP server.

Wrote 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.

agentmods badge for eval-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/goodeye-labs/truesight-mcp-skills/eval-audit/github.svg)](https://agentmods.dev/skills/goodeye-labs/truesight-mcp-skills/eval-audit)
Your own site
<a href="https://agentmods.dev/skills/goodeye-labs/truesight-mcp-skills/eval-audit"><img src="https://agentmods.dev/badge/skills/goodeye-labs/truesight-mcp-skills/eval-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.

agentmods 80×15 button for eval-audit

Your own site · 80×15
<a href="https://agentmods.dev/skills/goodeye-labs/truesight-mcp-skills/eval-audit"><img src="https://agentmods.dev/badge/skills/goodeye-labs/truesight-mcp-skills/eval-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 585 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.00585
Opus 5 $0.00020 $0.00293
Sonnet 5 $0.00008 $0.00117
Haiku 4.5 $0.00004 $0.00059

Measured 11d ago against content hash 763b5c2ad177, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

eval-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 11d 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.

skills/eval-audit/SKILL.md · 84 lines

How it starts

The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Eval Audit

Audit LLM evaluation practice and route gaps to the right skills.

Interactive Q&A protocol (mandatory)

Ask one question at a time using the structured question tool (loaded per the HARD-GATE above).

Example question structure:

What should this audit prioritize first?
A) Live evaluation quality and coverage
B) Error analysis maturity
C) Review and promotion loop health
D) End-to-end process health

Rules:

  • One question per message.
  • Use the structured question tool for every question. Structure each with a short header, 2-4 options with labels and descriptions, and place the recommended option first. Do not add "(Recommended)" or similar annotations to option labels.
  • Ask one follow-up only if ambiguity remains.

Inputs and evidence

Collect available evidence from Truesight first:

  • datasets and dataset rows
  • live evaluations
  • evaluation runs/results
  • review queue items
  • existing evaluation criteria and deployment patterns

If evidence is missing, record that as a finding.

Diagnostic areas

  1. Evaluation coverage and quality dimensions
  2. Error analysis practice and category quality
  3. Review and promotion workflow discipline
  4. Template usage versus custom needs
  5. Operational hygiene (verification, reruns, iteration cadence)

Report format (mandatory)

For each finding, include:

### <Finding title>
Status: Problem exists | OK | Cannot determine
Evidence: <specific evidence from Truesight context>
Severity: critical | high | medium | low
Recommended skill: <one of current skill set>
Next command: <concrete instruction to run next>

Order findings by severity and impact.

Severity rubric

  • critical: likely causes incorrect go/no-go decisions or severe user harm
  • high: frequent quality failures or missing control loops
  • medium: meaningful process weakness with moderate impact
  • low: optimization opportunity, documentation, or ergonomics issue

Read the full file on GitHub · 84 lines

Changes

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.

  1. 11d ago First seen · 84 lines · 40 tokens per session scan A 763b5c2ad177

Subscribe to this mod's changes

eval-audit is a skill published in the GitHub repository Goodeye-Labs/truesight-mcp-skills (7 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 585 once invoked, about $0.0002 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 2026-08-31.

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