BS
Brainstorming Skills Breakdown: Design Loop of Single-Step Clarification
bestskills rank team
2026-04-15

A comprehensive review of brainstorming skills. We break down its underlying Prompt logic in openclaw/hermes agent, showing how single-step clarification and progressive confirmation force AI to output rigorous design specs before coding.


Skill Quality Report: brainstorming

Evaluation Time: 2026-04-15
Evaluation Mode: Item-by-item review

Overall Score

DimensionScoreStatus
Standards (20%)15/20WARN
Effectiveness (40%)36/40PASS
Safety (30%)29/30PASS
Conciseness (10%)8/10WARN
Total88/100Good

Level guide:

  • 90-100: Excellent — ready to use
  • 70-89: Good — small but meaningful room to improve
  • 50-69: Fair — needs important revisions
  • <50: Not qualified — requires substantial rewrite

Skill Strengths

  1. [Effectiveness] The design-before-code guardrail is explicit and enforceable — Evidence: Do NOT invoke any implementation skill... until you have presented a design and the user has approved it. (opening policy section)
  2. [Effectiveness] The workflow is operational, not just conceptual — Evidence: Checklist ... complete them in order (Checklist section)
  3. [Effectiveness] The terminal state is constrained to one downstream skill — Evidence: The ONLY skill you invoke after brainstorming is writing-plans. (Process Flow section)
  4. [Safety] It proactively blocks a common shortcut failure mode — Evidence: Anti-Pattern: "This Is Too Simple To Need A Design" (Anti-Pattern section)

Skill Improvement Areas

  1. [Standards] Frontmatter governance metadata is still thin — Evidence: frontmatter currently emphasizes name and description; Impact: weaker version traceability and weaker consistency across multi-skill repositories.
  2. [Effectiveness] Dependency intent is clear but not machine-readable — Evidence: ...invoke after brainstorming is writing-plans.; Impact: automation pipelines cannot reliably parse dependency chains from prose alone.
  3. [Conciseness] The main file carries too much in one place — Evidence: checklist, graph, anti-patterns, and long process notes are all in one body; Impact: higher token load and slower scanning in long sessions.

Insights

  1. Hard guardrails reduce implementation drift more effectively than soft reminders. — Application: planning-first and review-first skills.
  2. Naming anti-patterns directly helps teams catch shortcuts early. — Application: workflows where users often skip quality gates.
  3. A state-machine style flow is excellent for approval loops and strict terminal transitions. — Application: multi-step skills with rollback/review cycles.

Issue List

[Medium] Standards — Missing governance metadata

  • Location: frontmatter
  • Description: key fields like version, author, license, and structured metadata are missing.
  • Suggestion: add a full governance block and keep it versioned with each skill update.

[Medium] Effectiveness — Dependency is prose-only

  • Location: terminal-step policy in Process Flow
  • Description: dependency on writing-plans is mandatory but only expressed in text.
  • Suggestion: add a machine-readable dependency field (for example, related_skills).

[Low] Conciseness — Progressive disclosure can be stronger

  • Location: main document body
  • Description: detailed explanations are dense for frequent runtime loading.
  • Suggestion: move stable long-form guidance to reference/ and keep the main file focused on triggers and hard rules.

Prioritized Recommendations

  1. [Must] Complete frontmatter governance fields to improve maintainability and discoverability.
  2. [Should] Add machine-readable dependency metadata for writing-plans.
  3. [Could] Split long explanatory content into reference files to lower token cost.

Related Resources

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