episode-complete（剧集完成）

Episode Complete

Complete and score a learning episode to extract patterns and update heuristics.

Purpose

Finalize an episode with outcome scoring, reflection generation, and pattern extraction for future retrieval.

Steps

1. Gather outcome data:

- Final verdict (success, partial_success, failure) - Total time spent - Total tokens used (if applicable) - Key artifacts produced - Errors encountered

1. Create TaskOutcome: let outcome = TaskOutcome {verdict: Verdict::Success, time_ms: total_time, tokens: total_tokens, artifacts: vec![/* paths to created/modified files */], errors: vec![/* any errors encountered */],};
2. Call complete_episode: memory.complete_episode(episode_id, outcome).await?;
3. System processes:

- Computes RewardScore based on: - Success/failure - Time efficiency - Code quality - Generates Reflection: - What worked well - What could be improved - Key learnings - Extracts Patterns: - Tool sequences - Decision points - Common pitfalls

1. Update storage:

- Store in Turso (permanent record) - Update redb cache - Index by task_type and timestamp - Update related patterns and heuristics

1. Validation:

- Verify episode was scored - Check patterns were extracted - Ensure heuristics were updated

Pattern Types Extracted

• ToolSequence: Common tool usage patterns
• DecisionPoint: Key decision moments and outcomes
• ErrorPattern: Common errors and resolutions
• PerformancePattern: Optimization opportunities

Scoring Rubric

• Success: Task completed, tests pass, meets requirements
• Partial Success: Task mostly complete, minor issues
• Failure: Task incomplete, major issues, tests failing

Example

let outcome = TaskOutcome {
    verdict: Verdict::Success,
    time_ms: 45000,
    tokens: 12000,
    artifacts: vec![
        "src/storage/batch.rs".to_string(),
        "tests/integration/batch_test.rs".to_string(),
    ],
    errors: vec![],
};

memory.complete_episode(episode_id, outcome).await?;

Post-Completion

• Patterns are now available for future retrieval
• Heuristics updated for similar tasks
• Episode stored for long-term learning
• Embeddings computed (if service configured)