session-corpus-audit

name	session-corpus-audit
description	Analyze session quality trends — identify high-churn patterns, report waste, flag sessions exceeding 500 tool calls
version	1.0.0
category	coordination
tags	["session","audit","quality","signals"]
related_skills	["session-start-routine","comprehensive-learning"]

Session Corpus Audit

Analyze session signals to identify quality trends and waste patterns.

Data source

Session signals live at .claude/state/session-signals/YYYY-MM-DD.jsonl. Each line is a JSON object with: session_id, transcript_path, cwd, permission_mode, hook_event_name, stop_hook_active, last_assistant_message.

Audit procedure

1. Collect recent signals

# Last 7 days of session signals
for f in $(ls -t .claude/state/session-signals/*.jsonl | head -7); do
  echo "=== $(basename $f) ==="
  wc -l "$f"
  cat "$f"
done

2. Identify high-churn sessions

• Sessions that fired multiple Stop hooks (restarts/crashes)
• Sessions with last_assistant_message indicating errors or blocks
• Sessions ending with permission denials

3. Estimate tool-call volume

• Check .claude/state/session-governor/tool-call-count for daily totals
• Flag any day exceeding 500 tool calls (potential runaway session)

4. Detect recurring patterns

• Same error messages across sessions (systemic issues)
• Sessions that ended mid-task (unreleased wip labels, uncommitted changes)
• Permission mode patterns (bypassPermissions vs default)

5. Produce quality report

Output a markdown report with:

• Session count by day (last 7 days)
• High-churn sessions with root cause
• Recurring error patterns
• Waste estimate (sessions that produced no commits)
• Recommendations for workflow improvement

When to use

• Weekly quality review
• After a day with many session restarts
• When investigating tool-call ceiling hits
• When a product/chatbot already has rated conversation examples and the user asks to review provider sessions to catch up on inconsistencies

Conversation-rating provider catch-up

When auditing Claude/Codex/Hermes/Gemini sessions for a chatbot or product with existing conversation ratings, load the rated baseline first and treat provider logs as meta-evidence. Do not restart the rubric. Review provider sessions for workflow defects that explain or predict conversation-quality failures: delivery-state overclaims, internal/tool leakage, canary-before-live drift, channel/scope/domain terminology confusion, and user-blame before log inspection.

Use references/conversation-rating-provider-catchup.md for the detailed procedure and output shape.