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eval-engineering

Review, improve, and author MoltNet evals — one discipline across every use case (agent-runtime prompt evals in evals-v2/, practice/incident evals in evals/moltnet-practices/, and context-pack evals). Use when asked to "review an eval", "is this eval trustworthy", "improve/rewrite an eval scenario", "write an eval", "create an eval from an incident", "check the baseline", or "gap-test". Merges the LangChain eval-engineering process with MoltNet's battle-tested gap-test principles and the two-stage gate+judge harness.

Quality

92%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-5

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

A well-engineered instruction skill: a crisp two-stage model, a sequenced method with explicit validation and re-run criteria, concrete thresholds and anti-patterns drawn from real failures, and clean one-level-deep progressive disclosure into three substantive reference files. The main room for improvement is trimming the opening justification paragraph and inlining one full example command for the baseline runner.

DimensionReasoningScore

Conciseness

The body is dense and project-specific (gates/judge split, thresholds, anti-patterns) with little that Claude already knows, assuming competence throughout ("Read the target response, tool calls, gate evidence, and verdict"). Not a 5 because the opening rationale ("This skill exists because evals were fragmented into three shapes...") and a few transitions could be trimmed without losing guidance.

4 / 5

Actionability

Concrete, executable guidance throughout: observable behavior examples ("regenerates the Go client after a schema change"), hard thresholds ("≥40% of a judged score must require articulation", "≥2 for a gate check, ≥4 for reporting"), named runners and paths, a defined output format ("per-scenario verdict (keep / fix / cut)... most-severe first"), and a gold-standard example to study. Not a 5 because full command invocations for running baselines are only named, not shown inline.

4 / 5

Workflow Clarity

The Method is a clearly ordered 7-step sequence with explicit validation (step 6: "Measure the baseline; never estimate it" with run-count floors), an explicit feedback loop (step 7: "Re-run when the task was unclear, the environment unrealistic, the verifier wrong, or infra failed"), a human checkpoint (step 2: "let the human pick"), and a checklist for the review workflow — matching the top anchor.

5 / 5

Progressive Disclosure

SKILL.md is a ~100-line overview that cleanly splits detail into three real, one-level-deep references, each clearly signaled with what it contains ("Details and field schemas", "the five principles", "which incidents qualify... and the leakage guard"); verified all three files exist in references/ with no deep nesting.

5 / 5

Total

18

/

20

Passed

Description

95%Weight 40%Scale 1-5

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 description: concrete capabilities, a well-scoped niche, and an explicit 'Use when' clause with seven realistic trigger phrases including synonyms. The only mild weakness is that the capability verbs (review/improve/author) are fewer and less granular than the domain paths that qualify them.

DimensionReasoningScore

Specificity

Names three concrete actions ("Review, improve, and author MoltNet evals") and enumerates the three target corpora with concrete paths ("evals-v2/", "evals/moltnet-practices/", context-pack evals). Not a 5 because the action verbs themselves are fewer and more generic than the comprehensive multi-action lists in the top anchor.

4 / 5

Completeness

Explicitly answers both what ("Review, improve, and author MoltNet evals — one discipline across every use case") and when ("Use when asked to 'review an eval'..." with concrete trigger phrases), matching the top anchor exactly.

5 / 5

Trigger Term Quality

Quotes seven natural user phrasings — "review an eval", "is this eval trustworthy", "improve/rewrite an eval scenario", "write an eval", "create an eval from an incident", "check the baseline", "gap-test" — covering synonyms and variations a user would actually say.

5 / 5

Distinctiveness Conflict Risk

"MoltNet evals" is a clear niche and every trigger is eval-specific, so conflict risk with other skills is minimal; it even states it supersedes "legreffier-eval" to remove overlap with the prior system.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

getlarge/themoltnet

Path

.agents/skills/eval-engineering/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.