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skill-upper

Capture and review Agent Skill observations, and create, run, diagnose, or iteratively improve Skill evaluations (evals) with the skill-up CLI. Use when the user asks to record explicitly attributed Skill usage or feedback; review observations; turn an approved observation into a regression case; evaluate, test, regress, verify, fix, improve, iterate, or evolve a Skill; add or strengthen eval cases; write eval.yaml/case.yaml; run skill-up run/validate/list-cases/report/import/init; or migrate from Anthropic evals.json. Observation capture and review require either the Codex skill-up plugin or an observer-enabled DSH skill-up plugin; evaluation remains multi-engine.

76

Quality

95%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

92%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.

Highly actionable content: copy-paste-ready commands, expected outputs, a strictly sequenced workflow with validation and feedback loops, and clean progressive disclosure to real bundle files. The only notable weakness is moderate redundancy in the Language Policy section and the thrice-repeated install command.

Suggestions

Collapse the three near-identical 'curl -fsSL ... install.sh | bash' invocations in Step 0 into one command with a short note on the optional SKILL_UP_VERSION / INSTALL_DIR env vars.

Merge overlapping rules in 'Language Rules for Generated Artifacts' (e.g., the CJK self-check and the English-assertion rules restate the same constraint) into a single compact checklist.

DimensionReasoningScore

Conciseness

The body is largely lean — exact commands, terse bullets, tables — but the Language Rules section is repetitive and Step 0 repeats the identical 'curl -fsSL ... install.sh | bash' three times in a row. It is noticeably above the midpoint (efficient with only minor trim opportunities), not fully lean at anchor 5.

4 / 5

Actionability

Fully executable guidance throughout: exact bash commands (skill-up validate/run/init/import with flags), expected output ('✓ eval.yaml is valid (loaded N case(s))'), exit-code semantics (0/1 for CI), artifact paths, and a flags/commands quick-reference table.

5 / 5

Workflow Clarity

A strictly ordered Step 0–8 main flow with an explicit validation checkpoint (Step 4 validate with expected output), a stop-and-ask credential gate (Step 5), and a diagnose→fix→rerun feedback loop in Step 8 with 'do not weaken valid assertions' and continue-until-pass guidance.

5 / 5

Progressive Disclosure

The body is a clear overview with well-signaled, one-level-deep references; all cited files exist (references/install.md, observations.md, eval-yaml.md, case-yaml.md, judge-types.md, cli.md, migrate-anthropic.md, and assets/eval.yaml.tmpl, assets/case.yaml.tmpl), each referenced where it is needed.

5 / 5

Total

19

/

20

Passed

Description

96%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: comprehensive concrete capabilities, explicit 'Use when' triggers with natural synonyms, and a clearly staked-out niche around skill-up evaluation tooling. The only weakness is that broad improvement verbs ('fix/improve/evolve a Skill') slightly inflate overlap risk with generic skill-maintenance skills.

DimensionReasoningScore

Specificity

The description lists many concrete actions — 'Capture and review Agent Skill observations', 'create, run, diagnose, or iteratively improve Skill evaluations (evals)', 'write eval.yaml/case.yaml', 'migrate from Anthropic evals.json' — covering the skill's capabilities comprehensively in third-person voice.

5 / 5

Completeness

Both 'what' (capture/review observations; create, run, diagnose, or improve evals with the skill-up CLI) and an explicit 'Use when the user asks to...' clause with concrete trigger phrases are clearly present, matching the top anchor exactly.

5 / 5

Trigger Term Quality

Trigger terms are natural user phrasings with synonyms ('evaluate, test, regress, verify, fix, improve, iterate, or evolve a Skill', 'record... Skill usage or feedback', 'add or strengthen eval cases') plus concrete file names (eval.yaml, case.yaml, evals.json). Not score 4 because no common natural variation is missing.

5 / 5

Distinctiveness Conflict Risk

The skill-up eval-tooling niche is distinct with tool-specific triggers, but broad verbs like 'fix, improve, iterate, or evolve a Skill' could also match generic skill-editing skills, creating minor overlap risk — fits anchor 4 better than 5.

4 / 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

LuminairPrime/git-worktrees-prime

Path

.agents/skills/skill-upper/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.