eagle3-validate

Validate that an EAGLE3 pipeline run completed successfully end-to-end. Checks all 4 steps produced expected artifacts, verifies acceptance rate meets threshold (>= 2.1), and produces a summary report. Use when user wants to verify a pipeline run or check benchmark results.

Quality

92%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

100%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, highly actionable validation workflow with concrete commands, exact log signatures, explicit validation gates, and a ready-to-use report template. It respects the context budget and sequences a multi-step pipeline check with clear feedback loops.

Dimension	Reasoning	Score
Conciseness	Lean and token-efficient: jumps straight into commands, tables, and exact log signatures without explaining what EAGLE3 is or how logging works, assuming Claude's competence throughout.	3 / 3
Actionability	Fully executable guidance — concrete bash ('ls -td experiments/cicd/cicd_*', 'find ... tail -50'), exact log strings to grep ('Average Acceptance Length {... ratio: Z.ZZ}', 'DUE TO TIME LIMIT'), explicit artifact paths, and a copy-paste report template.	3 / 3
Workflow Clarity	Clear 6-step sequence with explicit validation checkpoints (pass/fail/timeout signals in Step 1, a PASS/FAIL threshold table in Step 3) and a feedback loop ('If any task failed, suggest running /eagle3-triage').	3 / 3
Progressive Disclosure	Self-contained single-file skill with well-organized numbered sections, tables, and templates; no nested or deeply chained references, appropriate for a focused validation checklist.	3 / 3
	Total	12 / 12 Passed

Description

85%Weight 40%Scale 1-3

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, concrete description that clearly states both capability and trigger conditions, scoped to a distinct niche. The main weakness is trigger-term breadth — it covers the obvious phrasings but omits common synonyms a user might naturally say.

Suggestions

Broaden the 'Use when' clause with common natural phrasings, e.g. 'validate a run', 'did the run pass', or 'check acceptance rate / AR'.

Consider naming the key metric users reference ('acceptance rate') directly in the trigger rather than only 'benchmark results'.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Checks all 4 steps produced expected artifacts, verifies acceptance rate meets threshold (>= 2.1), and produces a summary report' — rather than vague language.	3 / 3
Completeness	Explicitly answers both what it does ('Validate... Checks all 4 steps... verifies acceptance rate... produces a summary report') and when to use it via a clear 'Use when' clause.	3 / 3
Trigger Term Quality	Includes relevant natural triggers ('verify a pipeline run', 'check benchmark results') but misses common variations users might say ('validate', 'did my run pass', 'acceptance rate').	2 / 3
Distinctiveness Conflict Risk	Targets a specific niche (EAGLE3 pipeline, 4 steps, AR >= 2.1) with distinct triggers unlikely to fire for unrelated skills.	3 / 3
	Total	11 / 12 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: NVIDIA/Model-Optimizer
Path: .agents/skills/eagle3-validate/SKILL.md
Commit: 87c9f8c

Reviewed: 15 days ago

Table of Contents

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