oduffy-delphi/coordinator:eval-output
skills/eval-output/SKILL.md
Score a research output against the 5-criteria eval rubric. Dispatches a Sonnet evaluator.
$ install --global
skillsauthnpx skillsauth add oduffy-delphi/coordinator-claude coordinator:eval-outputInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Jul 11, 2026, 7:51 AM141.2s1 file scanned
SKILL.md
- name:
- coordinator:eval-output
- description:
- Score a research output against the 5-criteria eval rubric. Dispatches a Sonnet evaluator.
Evaluate Research Output
Usage
/coordinator:eval-output <path-to-research-output>
Process
- Read the eval rubric at
${CLAUDE_PLUGIN_ROOT}/pipelines/deep-research/eval-rubric.md
- Read the research output at the provided path
- Dispatch a Sonnet agent (model: sonnet, tools: Read, WebFetch, Write) with:
- The rubric
- The research output
- Instruction to: read the output, sample 3-5 cited URLs via WebFetch to verify citation accuracy, score each of the 5 criteria with a 0.0-1.0 score and 2-3 sentence justification, provide overall pass/marginal/fail grade
- Present the scores to the PM
Notes
- This is a post-hoc quality check, not a gate. Use it to calibrate prompt improvements.
- Start by running it on recent pipeline outputs to establish a baseline.
- Anthropic found a single LLM call with a single prompt was most consistent.
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