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app-evolver

Improves an existing application using its code, product contract, authorized work history and competitor evidence. Use for 取长补短、取其精华去其糟粕、参考竞品优化应用 or evolving an app from successful and failed work. Carries authorized changes through implementation and user-result verification, including REA and reverse Skill composition; use skill-evolver for Skills.

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

81%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-structured orchestration skill with a clear five-phase workflow, explicit validation and error-recovery loops, and disciplined use of reference files. Its main weaknesses are a moderate amount of abstract policy prose and one reference file buried at a second nesting level.

DimensionReasoningScore

Conciseness

The body contains no explanations of concepts Claude already knows and is densely directive, but authorization/boundary statements recur across sections and some aphoristic policy sentences ('A failed parameter family is not a reason to try indefinitely') could be trimmed.

4 / 5

Actionability

Concrete guidance includes the six-row decision-input table, exact read-triggers for each reference file, and specific routing rules ('Pin the code used for judgment to an immutable ref'), though a share of directives remain abstract principles and no examples of falsifiable acceptance criteria or probes are given.

4 / 5

Workflow Clarity

Five clearly sequenced phases (bind, ground, decide, implement, verify/deliver) with an explicit error-recovery feedback loop ('When evidence fails, inspect raw signals, seek a falsifier and correct the root cause') and calibration of new guards on healthy and failing inputs, plus gated destructive/deployment boundaries.

5 / 5

Progressive Disclosure

Four one-level references are each well-signaled with when-to-read context and valid anchors, but feature-investigation.md is only reachable via a second-level link inside skill-composition.md and is never surfaced in the overview, so navigation is not perfectly one-level-deep.

4 / 5

Total

17

/

20

Passed

Description

83%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 with an explicit 'Use for' trigger clause in third person, a clear capability statement, and an explicit boundary to a sibling skill. Slight improvements are possible by adding English trigger synonyms and unpacking the 'REA' abbreviation.

DimensionReasoningScore

Specificity

Names the domain plus several specific actions and inputs ('implementation and user-result verification, including REA and reverse Skill composition'), but the core verb 'improves' stays abstract and 'REA' is unexplained jargon, leaving minor coverage gaps.

4 / 5

Completeness

Explicitly answers both what ('Improves an existing application using its code, product contract, authorized work history and competitor evidence... through implementation and user-result verification') and when ('Use for 取长补短... or evolving an app from successful and failed work') with concrete trigger phrases, plus a routing boundary to skill-evolver.

5 / 5

Trigger Term Quality

Natural trigger phrases users would say are present (取长补短、取其精华去其糟粕、参考竞品优化应用, 'evolving an app from successful and failed work'), but common English variations such as 'optimize my app' or 'learn from competitors' are missing.

4 / 5

Distinctiveness Conflict Risk

A clear niche (evidence-driven evolution of an existing app) with explicit disambiguation ('use skill-evolver for Skills'), but 'improves an existing application' and 参考竞品 wording leave minor overlap risk with general coding-optimization or competitor-analysis skills.

4 / 5

Total

17

/

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

daymade/claude-code-skills

Path

app-evolver/SKILL.md

Reviewed

Table of Contents

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