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Eval audit

Skill Goodeye-Labs/truesight-mcp-skills/skills/eval-audit

Audit an existing evaluation workflow and produce severity-ranked findings with concrete next actions. Use when inheriting an eval setup, diagnosing quality regressions, or checking LLM evaluation process maturity.From its SKILL.md

Install
npx -y skills add Goodeye-Labs/truesight-mcp-skills --skill eval-audit

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.8 KB, 543 tokens by cl100k_base, as published. Nobody here has run it

Eval Audit

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

Interactive Q&A protocol (mandatory)

<HARD-GATE> BEFORE the first scoping question, search for a structured question tool (e.g., `AskUserQuestion` or similar interactive widget) and load it. Use that tool for EVERY scoping question. Fall back to plain-text lettered options ONLY if no such tool exists in the environment. </HARD-GATE>

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

Handoff map

  • Missing or weak failure taxonomy -> error-analysis
  • Missing live evaluation coverage -> create-evaluation or bootstrap-template-evaluation
  • Review backlog or low judgment throughput -> review-and-promote-traces
  • Unclear starting path -> truesight-workflows

Guardrails

  • Keep scope within current Truesight MCP capabilities.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.