.claude/skills/debug-log-analysis/SKILL.md
Structured debug log analysis for Claude Code sessions — auto-discovers most recent log, runs reducer, extracts error patterns, correlates with full log, produces observability report. Fills 5 identified gaps: hook error body capture, agent identity, file path tracking, stall correlation, success visibility.
npx skillsauth add oimiragieo/agent-studio debug-log-analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Mode: Cognitive/Prompt-Driven — No standalone utility script; use via agent context.
Structured workflow for extracting actionable signal from Claude Code session debug logs. Use during reflection cycles, incident response, or when diagnosing agent failures.
The scripts/reduce-debug-log.mjs script auto-detects the most recent log when no file argument is provided. It copies the log to .tmp/ and produces a reduced version there.
Two modes are available:
Auto mode (recommended): Let pnpm debug:reduce find and process the most recent log automatically.
Manual mode: Provide a specific session UUID or log file path.
IMPORTANT: Always find the most recent log dynamically. NEVER hardcode session UUIDs.
# Auto-detect most recent log, copy to .tmp/, reduce in place
cd /c/dev/projects/agent-studio && node scripts/reduce-debug-log.mjs 2>&1
# The script prints:
# Auto-detected debug log: /home/user/.claude/debug/{session-uuid}.txt
# Copied to: .tmp/{session-uuid}.txt
# Original: N lines -> kept (issue-like): M -> ... -> after dedupe: K
# Output: .tmp/{session-uuid}-reduced.txt
Capture the output paths from the script output for subsequent steps.
# List recent debug logs sorted by modification time (most recent first)
ls -t "$HOME/.claude/debug/"*.txt 2>/dev/null | head -5
# Or on Windows (Git Bash):
ls -t "$USERPROFILE/.claude/debug/"*.txt 2>/dev/null | head -5
Pick the target log path, then:
# Copy to temp (never operate on the original)
mkdir -p .claude/context/tmp
cp "$HOME/.claude/debug/{session-uuid}.txt" ".claude/context/tmp/debug-session-copy.txt"
# Run reducer with explicit output path
node scripts/reduce-debug-log.mjs \
".claude/context/tmp/debug-session-copy.txt" \
--output ".claude/context/tmp/debug-session-reduced.txt"
# Check sizes
wc -l ".claude/context/tmp/debug-session-copy.txt"
wc -l ".claude/context/tmp/debug-session-reduced.txt"
Expected: reduced file is 1-5% of original line count (98%+ noise removed).
Calculate what was filtered out to understand the filter quality:
ORIGINAL_LINES=$(wc -l < ".claude/context/tmp/debug-session-copy.txt")
REDUCED_LINES=$(wc -l < ".claude/context/tmp/debug-session-reduced.txt")
echo "Original: $ORIGINAL_LINES lines | Reduced: $REDUCED_LINES lines"
echo "Kept: $(echo "scale=1; $REDUCED_LINES * 100 / $ORIGINAL_LINES" | bc)%"
Note any anomalies — e.g., if reduction is less than 90%, the session had unusually many errors.
Read .claude/context/tmp/debug-session-reduced.txt in full.
For each line in the reduced log, classify into:
| Category | Signal Pattern | Action |
| --------------------------- | -------------------------------------------------------------- | ---------------------------------------- |
| Hook Block (Write) | PreToolUse:Write + block | Count; find triggering agent + file path |
| Hook Block (TaskUpdate) | PreToolUse:TaskUpdate + burst | Count; find looping agent |
| Read Miss | File does not exist or placeholder text | Count; list missing files |
| Token Overflow | FileTooLargeError or token limit | Count; identify large files |
| Streaming Stall | Gap > 60s between log entries | Sum duration; note what preceded stall |
| Agent Drop | TaskUpdate not called or agent returned without completion | List by task ID |
| Tool Error | EISDIR, ENOENT, sibling tool call errored | Categorize by tool |
For the top 3 most frequent error categories:
# Use the full copy (not the original, not the reduced)
grep -n "PreToolUse:Write" ".claude/context/tmp/debug-session-copy.txt" | head -30
grep -n "File does not exist" ".claude/context/tmp/debug-session-copy.txt" | head -30
grep -n "timeout" ".claude/context/tmp/debug-session-copy.txt" -i | head -30
After analysis, clean up the working copy (keep the reduced file for the report if needed):
rm -f ".claude/context/tmp/debug-session-copy.txt"
# Optionally keep the reduced file for reference; delete when done
# rm -f ".claude/context/tmp/debug-session-reduced.txt"
Write to .claude/context/reports/reflections/debug-log-analysis-{YYYY-MM-DD}.md:
<!-- Agent: reflection-agent | Skill: debug-log-analysis | Session: {YYYY-MM-DD} -->
# Debug Log Analysis — {YYYY-MM-DD}
**Source log:** {path to original log — auto-detected or provided}
**Session UUID:** {session-uuid extracted from filename}
**Log statistics:**
- Original: {N} lines / {bytes} bytes
- Reduced: {M} lines / {bytes} bytes
- Reduction ratio: {X}%
**Analysis timestamp:** {ISO-8601}
## Error Summary
| Category | Count | Severity | Root Cause |
| ------------------ | ----- | -------- | ---------- |
| Hook Block (Write) | N | CRITICAL | ... |
| Read Miss | N | HIGH | ... |
| ... | | | |
## Top 3 Deep Dives
### 1. {Most frequent error}
**Frequency:** N occurrences
**First occurrence:** line {N}, timestamp {T}
**Context:** {what the agent was doing}
**Root cause:** {why it happened}
**Fix:** {concrete recommendation}
### 2. ...
### 3. ...
## Observability Gaps Found
List any gaps where the log entry doesn't have enough info to diagnose the error.
## Recommendations
- [ ] Immediate P0: {fix}
- [ ] P1: {fix}
- [ ] P2: {fix}
These gaps exist in the current debug log format:
Hook rejection body not logged — When unified-creator-guard.cjs blocks a Write, the rejection reason is not captured in the debug log. You see PreToolUse:Write blocked but not WHY.
process.stderr output separately; or read the hook source to infer the rule that fired.Agent identity missing from error lines — Error lines don't include which spawned agent caused the error.
Read failure file path omitted — File does not exist lines don't always include the file path.
Streaming stalls unattributed — A 5+ minute stall appears as a timestamp gap with no context.
No success logging — Only failures are prominent. Successful tool calls produce minimal log entries.
Reflection agents should invoke this skill for HIGH-priority reflection requests:
// In reflection agent, for high-priority triggers:
if (priority === 'high' && debugLogPath) {
Skill({ skill: 'debug-log-analysis' });
// Include findings in reflection report
}
.claude/context/memory/issues.md — patterns not written to memory will recur invisibly across sessions.| Anti-Pattern | Why It Fails | Correct Approach |
| ----------------------------------------- | -------------------------------------------------------------------- | ----------------------------------------------------------------------------------- |
| Grepping the original log file directly | Modifies timestamps, corrupts forensic artifact, no rollback | Always copy first: cp debug.txt .claude/context/tmp/debug-{date}.txt |
| Reading the full unreduced log | 98%+ noise-to-signal ratio; analysis takes hours and misses patterns | Run reduce-debug-log.mjs first; work from the reduced output |
| Reporting root cause from single grep hit | Single matches are often false positives from unrelated tool calls | Read ±10 lines of context for every match before concluding root cause |
| Informal verbal summary instead of report | Reflection agent can't parse informal summaries into memory entries | Write the full structured markdown report to .claude/context/reports/reflections/ |
| Skipping memory writes after analysis | Error patterns recur invisibly; no institutional learning | Write every new pattern to issues.md or learnings.md before task complete |
After completing:
.claude/context/memory/issues.md.claude/context/memory/issues.md.claude/context/memory/learnings.mdASSUME INTERRUPTION: If it's not in memory, it didn't happen.
tools
Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.
tools
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
data-ai
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
development
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.