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brainstorm

Collaborative requirements discovery session optimized for AI coding workflows. Creates task directories, seeds PRDs, runs codebase research, proposes concrete implementation approaches with trade-offs, and converges on MVP scope through structured Q&A. Use when requirements are unclear, multiple implementation paths exist, trade-offs need evaluation, or a complex feature needs scoping before development.

68

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

A thorough, highly actionable requirements-discovery workflow with clear sequencing and concrete templates. Its weaknesses are redundancy (the PRD structure is repeated several times) and the lack of any file-splitting for a body well over 50 lines.

Suggestions

Move the reusable PRD, research-notes, and final-confirmation templates into reference files (e.g. references/prd-template.md) and link to them, leaving SKILL.md as a lean overview.

De-duplicate the PRD structure: define it once and reference that single source instead of restating Goal/Requirements/Acceptance Criteria/Out of Scope in three places.

DimensionReasoningScore

Conciseness

Largely actionable templates rather than concept explanations Claude already knows, but the PRD structure is repeated across Step 0, 'PRD Target Structure (final)', and the final confirmation format, which could be tightened.

2 / 3

Actionability

Provides concrete, copy-paste-ready bash commands ('python3 ./.trellis/scripts/task.py create ...') and complete markdown templates for PRDs, research notes, expansion sweeps, and final confirmation.

3 / 3

Workflow Clarity

Steps 0–8 are clearly sequenced with explicit gates (Gate A/B/C), a complexity classification table, question-priority ordering, and a final user-approval checkpoint in Step 8.

3 / 3

Progressive Disclosure

Well-organized with clear sections, but the skill is a ~488-line monolithic SKILL.md with no bundle files; reusable templates (PRD, research, confirmation) that could live in reference files are inlined.

2 / 3

Total

10

/

12

Passed

Description

85%

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, third-person description that concretely lists capabilities and provides explicit 'Use when' trigger guidance. The main weakness is trigger phrasing that is somewhat abstract rather than matching natural user speech.

Suggestions

Add colloquial trigger phrasings users actually say, e.g. 'Use when the user isn't sure what they want', 'there are several ways to build this', or 'a feature is too vague to start coding'.

Consider whether 'PRDs' and 'MVP scope' jargon should be softened or paired with plain-language equivalents for broader recognizability.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('Creates task directories, seeds PRDs, runs codebase research, proposes concrete implementation approaches with trade-offs, and converges on MVP scope through structured Q&A') rather than vague language.

3 / 3

Completeness

Clearly answers what it does (task dirs, PRDs, research, approaches, MVP) and when to use it via an explicit 'Use when...' clause with multiple triggers.

3 / 3

Trigger Term Quality

Triggers ('requirements are unclear', 'multiple implementation paths exist', 'trade-offs need evaluation', 'complex feature needs scoping') are relevant but lean conceptual/jargony and miss common colloquial variations a user might actually say.

2 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (pre-implementation requirements brainstorming for AI coding workflows) with concrete actions and distinct triggers unlikely to fire for unrelated skills.

3 / 3

Total

11

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
zhukunpenglinyutong/desktop-cc-gui
Reviewed

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