Debug
Skill that gives AI coding agents persistent memory and quality enforcement
npx -y skills add mattjaikaran/meridian --skill debugAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
2.3 KB, as published. Nobody here has run it
/meridian:debug — Systematic Debugging
4-phase systematic debugging with decision logging. Uses the protocol from references/discipline-protocols.md.
Arguments
<description>— Bug description or error message--plan <id>— Associate with a specific plan--phase <id>— Associate with a specific phase
Procedure
Phase 1: Investigation
- Read the full error message and stack trace
- Identify the exact file, line, and function
- Check recent changes:
git log --oneline -10andgit diff - Reproduce the error by running the failing test/command
- Record findings
Phase 2: Pattern Recognition
- Categorize the error type:
- Import/module error
- Type error / null reference
- Logic error / wrong behavior
- Race condition / timing
- Configuration / environment
- Data integrity
- Search codebase for similar patterns
- Check if this is a known issue pattern
Phase 3: Hypothesis
- Form a specific hypothesis: "The error occurs because X"
- Identify evidence that would confirm/refute
- Test with minimal change
- Record hypothesis and result as a decision:
PYTHONPATH=$MERIDIAN_HOME uv run --project $MERIDIAN_HOME -- python -c "
from scripts.db import connect, get_db_path
from scripts.state import create_decision
conn = connect(get_db_path('.'))
create_decision(conn, '<hypothesis and result>', category='approach',
rationale='<evidence>', phase_id=<phase_id_or_None>)
conn.close()
"
Phase 4: Implementation
- Fix at the source, not the symptom
- Run the failing test — must pass now
- Run full test suite — no regressions
- Commit the fix with descriptive message
Escalation Rule
After 3 failed fix attempts:
- STOP fixing
- Record a deviation decision
- Re-examine assumptions
- Consider if the problem is architectural
- May need to re-plan the current phase
PYTHONPATH=$MERIDIAN_HOME uv run --project $MERIDIAN_HOME -- python -c "
from scripts.db import connect, get_db_path
from scripts.state import create_decision
conn = connect(get_db_path('.'))
create_decision(conn, 'Escalation: 3+ failed fixes on <issue>. Likely architectural.',
category='deviation', rationale='<what was tried>')
conn.close()
"
Output
Report:
- Root cause identified
- Fix applied (file:line)
- Tests passing
- Decision logged