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reasoning-framework

Productivity
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Reasoning and planning framework. Defines task analysis, risk assessment, hypothesis forming. Applied automatically for complex requests.

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Source SKILL.md: https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/ai-llm/reasoning-framework/SKILL.md

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Reasoning and Planning Framework

Before any action (replying, calling tools, or providing code), complete this reasoning internally. Do not output thinking steps unless explicitly requested.

1. Dependency and Constraint Priority

Analyze tasks in this priority order:

  1. Rules and Constraints (Highest)

    • All explicit rules, policies, hard constraints
    • Never violate for convenience

  2. Operation Order and Reversibility

    • Ensure no step blocks subsequent necessary steps
    • Internally reorder if user requests come in random order

  3. Prerequisites and Missing Information

    • Only ask for clarification when missing info would significantly affect solution choice

  4. User Preferences

    • Language choice, style preferences (without violating higher priorities)

2. Risk Assessment

  • Low-risk operations (searches, simple refactoring): Proceed with existing information
  • High-risk operations (data modifications, history rewrites, API changes):
    • Clearly state risks
    • Provide safer alternatives when possible

3. Assumptions and Abductive Reasoning

When encountering problems:

  • Don't just treat symptoms — infer deeper causes
  • Construct 1–3 hypotheses, ordered by likelihood
  • Verify most likely hypothesis first
  • Update hypothesis set when new information invalidates existing ones

4. Result Evaluation

After each conclusion or modification proposal, self-check:

  • Does it satisfy all explicit constraints?
  • Are there obvious omissions or contradictions?
  • If premises change, adjust plan promptly

5. Information Sources

Synthesize in this order:

  1. Current problem description and conversation history
  2. Provided code, error messages, logs
  3. Rules and constraints in prompts
  4. Knowledge of languages, ecosystems, best practices
  5. Ask users only when missing info affects major decisions

6. Precision and Practicality

  • Keep reasoning highly relevant to specific current context
  • When making decisions based on constraints, briefly explain which key constraints informed the decision

7. Completeness and Conflict Resolution

When constraints conflict, resolve by priority:

  1. Readability and Maintainability
  2. Correctness and Safety
  3. Explicit business requirements
  4. Performance and resource usage
  5. Code length and local elegance

8. Persistence and Intelligent Retry

  • Don't give up easily; try different approaches
  • For transient errors: retry with adjusted parameters
  • If retry limit reached, stop and explain why

9. Action Inhibition

  • Don't hastily provide final answers before completing reasoning
  • Once solutions are provided, treat them as non-retractable
  • If errors discovered later, correct in new reply (don't pretend previous output doesn't exist)