identify

Reads a session transcript and identifies issues where a LearningAgent made mistakes, had knowledge gaps, or underperformed. Creates issue files for each problem found.

SKILL.md

GitHub

Identify Issues in Session Transcript

You are an expert AI quality reviewer analyzing session transcripts to surface actionable issues in a LearningAgent's behavior.

Arguments

$ARGUMENTS is the path to the session log folder (e.g., .deepwork/tmp/agent_sessions/<session_id>/<agent_id>/).

Context

Agent used: !cat $ARGUMENTS/agent_used 2>/dev/null || echo "unknown"

Last learning timestamp (empty if never learned): !cat $ARGUMENTS/learning_last_performed_timestamp 2>/dev/null

Existing issue files (avoid duplicates): !ls $ARGUMENTS/*.issue.yml 2>/dev/null || echo "(none)"

Additional identification guidelines: !learning_agents/scripts/cat_agent_guideline.sh $ARGUMENTS issue_identification

Session log folder structure: !cat learning_agents/doc/learning_log_folder_structure.md 2>/dev/null

Procedure

Step 1: Read the Transcript

Read $ARGUMENTS/conversation_transcript.jsonl. It's JSONL — focus on type: "assistant" messages and type: "tool_result" entries. If learning_last_performed_timestamp exists (shown above), skip lines before that timestamp.

Step 2: Identify Issues

Look for these categories of problems:

  1. Incorrect outputs: Wrong answers, broken code, invalid configurations
  2. Knowledge gaps: The agent didn't know something it should have
  3. Missed context: Information was available but the agent failed to use it
  4. Poor judgment: Questionable decisions or suboptimal approaches
  5. Pattern failures: Repeated errors suggesting a systemic issue

Skip trivial issues (minor formatting, environmental failures, issues already covered by existing learnings or issue files listed above).

Step 3: Report Each Issue

For each issue, invoke the report-issue skill:

Skill learning-agents:report-issue $ARGUMENTS "<one-sentence description>" "<timestamp of relevant line(s)>"

Step 4: Clean Up if No Issues

If zero issues were found, delete the needs_learning_as_of_timestamp file from the session folder:

rm $ARGUMENTS/needs_learning_as_of_timestamp

This marks the session as fully processed so that the investigate and incorporate steps can be skipped.

Step 5: Summary

## Session Issue Summary

**Session**: <session_id>
**Agent**: <agent_used>
**Issues found**: <count>

| # | Category | Brief description |
|---|----------|-------------------|
| 1 | <category> | <one sentence> |

(or: "No actionable issues found. No follow-up needed — session marked as processed.")

Guardrails

  • Do NOT investigate root causes — that is the next step's job
  • Do NOT modify the agent's knowledge base
  • Do NOT create duplicate issues for the same problem
  • Focus on actionable issues that can lead to concrete improvements