autonomous-gap-detector
Protocol for agents to autonomously detect skill gaps and maintain documentation health.
Installation
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
View source ↗GuidesSkill instructions
Autonomous Gap Detector Protocol
This protocol defines how an AI agent should autonomously manage skill gaps within a repository.
🤖 Agent Instructions (CRITICAL)
As an AI Agent, you are responsible for maintaining the "Documentation Health" of the project. You MUST trigger the Gap Detection process in the following scenarios:
- Task Initialization: When starting a new feature, scan for existing skills to see if you have the necessary knowledge.
-
Dependency Changes: Immediately after adding or updating any library (e.g., in
package.json,requirements.txt). - Task Completion (DoD Check): Before marking any task as "Done", you must verify that no new skill gaps were introduced.
Execution Protocol
When triggered, you must perform these steps:
-
Run Scanner: Execute the diagnostic script:
python d:\Cerebra\cerebraSkills\scripts\skill_watcher.py --target . -
Analyze
GAP_REPORT.md:- If RED GAPS are found:
- Analyze if the library is critical for the project's long-term maintenance.
- If it represents a new logic pattern, use the Skill Architect (
72-metacognitive-skill-architect) to draft a new skill. - Ask the user if they want you to finalize the new skill now or later.
- If ALL GREEN: Proceed with the task.
- If RED GAPS are found:
-
Cross-Reference: Check if the library is already in
LIB_MAPPINGinscripts/skill_watcher.py. If not, update the mapping to ensure future scans are accurate.
Reporting Logic
Any gaps identified should be reported to the user in this format:
"🚨 Skill Gap Detected: You are using
{library}, but we don't have a standardized Skill for it yet. This may lead to maintenance issues. Should I draft a Skill for this now?"
Technical Details
Scanner Script
- Location:
d:\Cerebra\cerebraSkills\scripts\skill_watcher.py - Config: Edit
LIB_MAPPINGto add new technology associations.
Logic Flow
- Parsing project dependency files.
- Filtering against
IGNORE_FILESandIGNORE_DIRS. - Matching against
SKILL_INDEX.mdentries. - Outputting markdown report to
GAP_REPORT.md.
Examples
Read the usage examples in the source repository.
View source ↗Source history
- Indexed on
- 2026-01-20
- Index updated
- 2026-01-26
- Branch
- main
Index and sync dates describe this directory. View the source repository for code history.
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