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SKILL verified MIT Self-run

Brainstorm

skill-cogni-ai-ou-cogni-ai-agent-skills-brainstorm · by Cogni-AI-OU

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Install

$ agentstack add skill-cogni-ai-ou-cogni-ai-agent-skills-brainstorm

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

✓ Security review passed
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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Skill brainstorm

A cognitive framework and protocol for exploring options, breaking down complexities, and summarizing information.

Core Process

  1. Context Gathering & Research: Aggressively gather facts, existing data, and constraints before formulating any conclusions.
  2. Explore Options: Generate multiple orthogonal approaches or alternative options. Do not settle for the first apparent solution.
  3. Deconstruct Complexities: Break down the problem space into atomic, manageable components.
  4. Visual Summarization: Synthesize the gathered data and complexities into simple, easy-to-read Mermaid diagrams (e.g., mindmaps, block diagrams, or flowcharts).

Core Principles

  • Design-It-Twice Protocol: ALWAYS generate at least two distinct architectural paths before recommending a preferred solution.
  • Divergent Before Convergent: Ensure a broad exploration of the problem space (divergent thinking) before narrowing down to specific recommendations (convergent thinking).
  • Fact-Based Exploration: Anchor all generated options in empirical data retrieved from the codebase, project memory, or provided context.
  • Recursive Decomposition: Break every complex objective into its atomic components to manage cognitive load and ensure precision.
  • Visual Clarity First: Use diagrams early to establish a shared mental model before diving into deep technical or textual analysis.

Diagnostics and Usage Patterns

  • Component Architecture Visualization: Map high-level structural components with a Mermaid block-beta diagram.
  • Context & Ecosystem Mapping: Map out the current ecosystem, constraints, and known unknowns using a Mermaid mindmap before defining architectural changes.
  • Diagramming Focus:

Default to high-level topological or structural diagrams (block-beta, flowchart, mindmap, quadrantChart, radar-beta) to visualize options and establish facts.

  • Flow & Logic Breakdown: Detail sequential states and dependencies using a Mermaid flowchart.
  • Root Cause & Priority Mapping: Use ishikawa-beta, quadrantChart, or radar-beta for evaluating alternatives, prioritization, and deep-dive problem exploration.

Brainstorming - Problem Breakdown

When you need to explore a complex problem, use this step-by-step visual approach to ensure all facts are gathered and complexity is reduced:

Step 1: Context & Ecosystem Mapping

Before proposing any changes, gather all relevant facts and constraints. Map the existing environment using a mindmap.

%% This diagram visualizes the existing ecosystem and constraints
mindmap
  root((System Context))
    Dependencies
      External API
      Database
    Constraints
      Performance
      Security
    Known Unknowns
      Rate limits

Step 2: Component Architecture Visualization

Break the problem into structural parts and orthogonal options using a block-beta diagram so the options can be compared effectively.

%% This block diagram shows multiple architectural options
block-beta
  columns 3
  space Option1 space
  FrontendA DatabaseA CacheA
  space Option2 space
  FrontendB DatabaseB CacheB

Step 3: Flow & State Modeling

Finally, visualize the behavior, state changes, or sequential logic required for the proposed options using a flowchart.

%% This flowchart explores a process logic option
flowchart LR
    Start --> CheckState{Is Valid?}
    CheckState -->|Yes| Process[Process Data]
    CheckState -->|No| Reject[Reject Request]

Step 4: Root Cause Exploration (If Applicable)

When brainstorming around a systemic issue or failure, use an ishikawa-beta (fishbone) diagram to aggressively deconstruct contributing factors before jumping to conclusions.

%% This diagram categorizes contributing factors to a problem
ishikawa-beta
    Core Problem or Failure
    Infrastructure
        Network latency
    Codebase
        Tech debt
        Missing tests
    Dependencies
        Deprecated API

Step 5: Prioritization Mapping

When multiple paths, options, or tasks are generated, map them onto a quadrantChart to evaluate trade-offs like effort versus impact.

%% This diagram visualizes task or option prioritization
quadrantChart
    title Option Prioritization
    x-axis Low Effort --> High Effort
    y-axis Low Impact --> High Impact
    quadrant-1 Quick Wins
    quadrant-2 Strategic
    quadrant-3 Time Sinks
    quadrant-4 Fill-ins
    "Option A": [0.2, 0.8]
    "Option B": [0.8, 0.9]
    "Option C": [0.7, 0.3]

Step 6: Trade-off Analysis

For complex architectural decisions, use a radar-beta diagram to score options across multiple competing dimensions.

%% This diagram scores options across various constraints
radar-beta
    title Architectural Trade-offs
    axis Performance, Security, Maintainability, Cost-Efficiency, Scalability
    curve Performance {8, 7, 6, 4, 9}
    curve Scalability {6, 9, 8, 7, 5}

What to Avoid

  • Assumption-Driven Brainstorming: Relying on guesses instead of factual context gathered through tools.
  • False Dichotomies: Assuming only two opposing solutions exist without exploring orthogonal architectural paths.
  • Overcomplicated Diagrams: Creating massive, unreadable diagrams. Break them into smaller, focused visual summaries.
  • Premature Convergence: Proposing a final solution without explicitly documenting the discarded alternative options.

Related Skills

  • brainstorm-agent-runs: You MUST load this skill when identifying agentic runs in CI/CD for a Pull Request.
  • brainstorm-github-pr: You MUST load this skill when asked to analyze or brainstorm a Pull Request.
  • critical-thinking: You MUST load this skill when evaluating the options generated during brainstorming.
  • mermaid: You MUST load this skill when constructing standard Mermaid diagrams.
  • mermaid-beta: You MUST load this skill when using experimental Mermaid diagrams.
  • minizinc: You MUST load this skill when executing or deeply modeling constraint satisfaction problems.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.