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Eval Audit

skill-goodeye-labs-truesight-mcp-skills-eval-audit · by Goodeye-Labs

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.

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Install

$ agentstack add skill-goodeye-labs-truesight-mcp-skills-eval-audit

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Eval Audit

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

Interactive Q&A protocol (mandatory)

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.

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:

### 
Status: Problem exists | OK | Cannot determine
Evidence: 
Severity: critical | high | medium | low
Recommended skill: 
Next command: 

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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.