# Experience Synthesis

> This skill should be used when the user asks to "learn from past sessions", "extract lessons", "find what worked", "identify patterns in my workflow", "what mistakes did I make", "what decisions were made", or wants to synthesize wisdom and actionable insights from conversation history.

- Skill: `xiaolai/experience-synthesis` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add xiaolai/experience-synthesis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/xiaolai/experience-synthesis/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: xiaolai (https://skillmd.com/u/xiaolai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/xiaolai/experience-synthesis

---


# Experience Synthesis — Learning from Claude's Past

## Insight Taxonomy

When analyzing conversations, extract insights in these categories (ordered by durability — values first):

### 1. Learned Values
Comparative preferences and priority orderings — "X is better than Y".

**Signal sources:**
- User states "prefer X over Y", "X is better than Y", "X matters more than Y"
- User confirms a comparative statement from Claude ("yes, readability > cleverness")
- Trade-off discussions that resolve into a clear preference
- Statements with "prioritize", "choose X over Y", "the most important thing is"

**What to capture:** The value choice, both sides of the comparison, and the reasoning. Values are the most durable type of memory — they survive codebase rewrites.

### 2. Decisions
What was chosen, why, and what alternatives were rejected.

**Signal sources:**
- `AskUserQuestion` tool calls + the user's response in the next tool_result
- Plan mode content (`planContent` field on user records, `ExitPlanMode` tool calls)
- Thinking blocks where Claude weighs options
- Assistant text containing "I'll use X instead of Y because..."

**What to capture:** The decision, the rationale, the alternatives considered, and the context (what problem it solved).

### 3. Mistakes & Corrections
What went wrong, root cause, and how it was fixed.

**Signal sources:**
- Tool results with `is_error: true`
- Bash results containing: error, failed, FAIL, exit code 1, stack trace, traceback, Exception
- User corrections: "no, that's wrong", "revert that", "that broke X"
- Retry patterns: same tool called 2+ times on the same target with different inputs
- Reverted file edits (same file edited, then edited back)

**What to capture:** What failed, why it failed, what fixed it, how to avoid it next time.

### 4. Effective Patterns
Approaches that worked well and could be reused.

**Signal sources:**
- Successful test runs (Bash results with: passed, PASS, success, 0 errors)
- Successful builds (built in, compiled, no errors)
- PR creation (`pr-link` records)
- Git commits (successful completion of work)
- User satisfaction signals: "perfect", "great", "exactly what I needed"

**What to capture:** The approach, when it applies, why it worked.

### 5. Anti-patterns
Approaches that failed, were abandoned, or caused problems.

**Signal sources:**
- Sequences where multiple attempts fail before finding a working solution
- Sessions with many compactions (long, possibly struggling sessions)
- Tool calls that were user-interrupted
- Files edited many times in one session (version count > 3 in file-history-snapshot)

**What to capture:** What was tried, why it failed, what worked instead.

### 6. User Preferences
The user's preferred tools, styles, and workflows.

**Signal sources:**
- Tool usage frequency across sessions (which tools does the user/Claude use most?)
- Model choices in sessions (opus vs sonnet vs haiku patterns)
- Permission mode patterns
- Common first prompts (workflow entry points)
- Branch naming conventions

**What to capture:** The preference, evidence across sessions, strength of pattern.

### 7. Architecture Knowledge
System design decisions, component relationships, tech stack details.

**Signal sources:**
- Early messages in sessions (problem descriptions, requirement discussions)
- Plan mode content (architectural plans)
- File paths touched across sessions (reveals project structure)
- Dependencies installed or configured

**What to capture:** Component, its role, relationships, key decisions about it.

### 8. Recurring Problems
Issues that keep coming back across sessions.

**Signal sources:**
- Similar error messages appearing in different sessions
- Same files being edited for fixes repeatedly
- Similar user prompts ("fix X again", "the Y bug is back")

**What to capture:** The problem, frequency, root cause pattern, whether it has a permanent fix.

### 9. Performance & Cost Patterns
Token usage trends, session efficiency, cost optimization opportunities.

**Signal sources:**
- `session-stats.sh` output across sessions: token totals, compaction counts
- Turn duration from `system` records with `subtype: turn_duration`
- Cache hit ratios (cache_read vs cache_creation tokens)
- Model selection patterns (when opus vs sonnet is used)

**What to capture:** Trends, outliers, optimization opportunities.

## Synthesis Methodology

When extracting insights, follow this process:

1. **Gather**: Use `list-sessions.sh` to identify relevant sessions, then `extract-messages.sh` and `extract-tools.sh` for detail
2. **Identify**: Look for signals from the taxonomy above
3. **Cross-reference**: Check if a pattern appears in multiple sessions (stronger signal)
4. **Contextualize**: Combine with git history when available (what code resulted from the decision/mistake?)
5. **Synthesize**: Produce actionable insights, not just observations

## Output Format

Present insights in a structured format:

```
## [Category]: [Brief Title]
**Sessions:** [session IDs or dates]
**Context:** [What was happening]
**Insight:** [The key learning]
**Evidence:** [Specific data points]
**Action:** [What to do differently / what to keep doing]
```

## Insight Quality Criteria

Good insights are:
- **Specific**: "Use --follow with git log when tracing renamed files" not "git is useful"
- **Actionable**: Something you can apply in future sessions
- **Evidenced**: Backed by data from multiple sessions when possible
- **Contextual**: Includes when the insight applies (and when it doesn't)

Skip insights that are:
- Generic programming advice (not specific to this user/project)
- One-time occurrences that aren't likely to recur
- Already documented in the project's CLAUDE.md or README