Skill Repair Assistant

You have been tasked with fixing a broken agent skill. After you have modified the skill's source files to address the reported error, you MUST update the manifest.json to reflect that the skill is now repaired.

Skill Context

• Skill ID: The unique identifier for the skill (e.g., my-skill).
• Source Path: Where the skill's source files are located.
• Installed Path: Where the skill is installed/replicated.
• Manifest Path: The absolute path to the manifest.json file.

Repair Procedure

1. Analyze Error: Understand the error message provided in the prompt.
2. Fix Installed Path: Fix the issue at the installed path. Since some skills have multiple files, you MUST list all files in the skill directory and analyze them collectively to find the root cause (e.g., malformed SKILL.md, missing resources, or incorrect sub-scripts).
3. Update Manifest: Once the fix is applied to ALL relevant files, you MUST update the manifest.json at the Manifest Path.
   • Find the entry for the skill ID in the skills object.
   • Set "status": "installed".
   • Clear the "error" field (set to null or remove it).
4. Verification: The UI will automatically detect this change and refresh.

Manifest Example

{
  "skills": {
    "my-skill": {
      "status": "installed",
      "disabled": false,
      "error": null
    }
  }
}

Anti-Patterns

Avoid	Why	Instead
Modifying manifest without source fixes	Re-triggers installation failures on reload	Resolve compilation bugs in target source files first
Saving malformed JSON files	Crashes the main UI parser framework	Run a JSON validate syntax check (python -m json.tool) before saving

References

MANDATORY - Self-containment Directive: This is a self-contained skill. Do NOT load external files or reference directories unless explicitly created during the execution of this workflow.

Memory Sync

After completing key technical findings, architectural decisions, code refactorings, or risk assessments, you MUST trigger the local memory capture.

1. Save the final summary or artifact as a Markdown file in the project directory.
2. Invoke the capture script:

   python3 ~/memory_system/capture_knowledge.py <file_path>
   

3. This ensures that new learnings, policies, and technical snippets are automatically routed to the correct local storage (OKF or ChromaDB).