name: experience-crystallizer description: Analyze current session history to learn from mistakes and crystallize a new skill. Use this when you successfully solved a hard problem after trial and error, and want to save the solution for future use. tools:

• name: find_current_session_context description: Locate the physical path of the current session's log file (context.jsonl). MUST be called with a unique fingerprint string. parameters: properties: fingerprint: description: A unique random string (e.g. UUID) that you MUST generate and include in this tool call. type: string required: - fingerprint command: /Users/moonshot/.local/share/uv/tools/kimi-cli/bin/python3 skills/experience-crystallizer/scripts/locate_context.py {fingerprint}

• name: analyze_session_log description: Read and summarize the session log to extract user intent, errors, and successful actions. parameters: properties: path: description: The absolute path to the context.jsonl file. type: string required: - path command: /Users/moonshot/.local/share/uv/tools/kimi-cli/bin/python3 skills/experience-crystallizer/scripts/analyze_log.py {path}

• name: validate_generated_skill description: Check if the generated skill complies with the Agent Skills specification. parameters: properties: path: description: The absolute path to the directory of the newly created skill. type: string required: - path command: /Users/moonshot/.local/share/uv/tools/kimi-cli/bin/python3 skills/experience-crystallizer/scripts/validate_skill.py {path}

Experience Crystallizer

This skill enables you to perform Self-Learning by creating standardized skills compliant with the Agent Skills Specification.

Trigger Criteria (WHEN TO USE)

CRITICAL: Do NOT use this skill for trivial tasks.

You should ONLY use this skill if the current session meets at least one of these criteria:

1. Trial & Error: You failed at least once (e.g., SyntaxError, logic error, wrong API usage) and had to fix it.
2. Discovery: You had to read external documentation or search the web to find a non-obvious solution.
3. Complexity: The solution required multiple steps or specific configurations that are hard to remember.

If the task was completed successfully on the first try with common knowledge, DO NOT create a skill.

Workflow (Decision Flow)

graph TD
    A[Start] --> B[Generate Fingerprint]
    B --> C[Locate Context]
    C --> D[Analyze Log]
    D --> E[Identify Solution]
    E --> F[Generate Skill Files]
    F --> G[Validate Skill]
    G -->|Pass| H[Done]
    G -->|Fail| I[Fix & Retry]
    I --> G

Output Specification (Agent Skills Standard)

You must create the new skill in skills/learned/<skill-name>/ with the following structure.

1. Directory Structure

skills/learned/<skill-name>/
  ├── SKILL.md            # [Required] Entry point
  ├── scripts/            # [Optional] Executable tools (was helpers/)
  ├── references/         # [Optional] Detailed docs
  └── assets/             # [Optional] Static resources
      └── examples/       # [Recommended] Read-only code (.example)

2. Validation Rules (Strict)

• Name: SKILL.md frontmatter name must match the directory name. Lowercase, hyphens only.
• Code Isolation: Files in assets/examples/ MUST end with .example.
• Executable: Place agent tools in scripts/.
• Documentation:
  • Keep SKILL.md concise (< 500 lines).
  • Use Mermaid flowcharts for logic.
  • Include ## Common Pitfalls.

Step-by-Step Implementation

1. Read log analysis.
2. Determine Root Cause & Solution.
3. Write SKILL.md and auxiliary files.
4. RUN validate_generated_skill. Fix any errors reported.