| name | review-chats |
| description | Use when the user wants to analyze their Claude Code chat history for recurring patterns, forgotten threads, or skill-abstraction candidates ("review my chats", "abstract skills from chat logs", "what am I repeating", "find patterns in my Claude sessions", "retro my chat history"). |
review-chats
Analyze Mike's Claude Code chat history (~133 project corpuses at ~/.claude/projects/) to surface recurring workflows that could become skills. Self-bootstrapping — uses parallel Explore subagents to avoid blowing up the main context.
PAIRED WITH: When a candidate is selected, chain into new-skill to scaffold it.
REQUIRED BACKGROUND: Uses superpowers:dispatching-parallel-agents pattern — up to 3 Explore agents in parallel, each with a disjoint slice of the corpus.
When to Use
Use when the user asks:
- "review my chats for patterns"
- "abstract skills from my chat logs"
- "what am I repeating across projects"
- "find skill candidates" / "what should I skill-ify"
- "retro my chat history"
Do NOT use when:
- The user wants to find a specific past conversation (use grep / search directly)
- The user wants today's chat only (too small a corpus)
- The user wants metrics (token counts, durations) — out of scope here
Corpus Structure
Each chat log is at ~/.claude/projects/<slug>/<session-uuid>.jsonl. Lines are JSON objects; user messages have "type":"user". The first user message of each session is the session-intent signal — most informative per byte.
Total scope (as of 2026-04): ~133 project dirs, mostly small. A handful are large (SignLab-Dev 331MB, superpowers 11MB, etc.) — weight sampling by corpus size.
Workflow
-
Scope the corpus. Default: all of ~/.claude/projects/. If the user specifies a project filter ("in roxas") or date range ("last month"), narrow accordingly.
-
Partition the corpus into 3 clusters for parallel analysis:
- Cluster A: most recently active (last 2 weeks by mtime)
- Cluster B: largest by bytes (top 5 dirs by
du -sh)
- Cluster C: the rest (sample evenly)
-
Dispatch 3 Explore subagents in parallel — one per cluster. Each agent's prompt:
- Lists the specific project dirs it owns
- Asks it to extract first-user-messages and look for phrasing patterns
- Asks it to report in under 400 words: pattern name, frequency, 2-3 verbatim examples, proposed skill scope
- Explicitly lists the CURRENTLY INSTALLED skills (pass them in) so the agent can filter out already-covered patterns
-
Merge & dedupe the three reports. Patterns surfaced by 2+ agents are high-confidence.
-
Cross-check against installed skills. Run ls ~/.claude/skills/ && ls /Users/mikelady/dev/mike-skills/ and compare trigger phrases in candidate descriptions. Drop any candidate whose triggers heavily overlap with an existing skill.
-
Present candidates via AskUserQuestion (multi-select). Each option shows: pattern name, frequency, one example. Include an "add your own" by letting Mike reply with "Other".
-
For each selected candidate: chain into the new-skill skill to scaffold it.
Signal Extraction Heuristics
Pass these hints to the subagents:
| Signal | What it means |
|---|
| Same opening phrase across ≥3 sessions (e.g., "install https://...") | Strong skill candidate |
| Repeated tool-use sequences (Bash → Grep → Bash) | Workflow worth abstracting |
| First user message is long and highly structured | Often a template the user re-types |
| Terms like "again", "like last time", "the usual" | User is doing repeat work |
| Sessions ending mid-stream (assistant tool calls, no user response) | Forgotten threads, not patterns |
Getting the Installed-Skills List
Pass this into every subagent prompt so they can filter:
( ls ~/.claude/skills/ ; ls /Users/mikelady/dev/mike-skills/ ) | sort -u
Output Format
After all subagents report:
Found N candidate patterns (M after filtering against installed skills):
1. <pattern-name> — <frequency>
Example: "<verbatim user message>"
Proposed scope: <one sentence>
2. ...
Then use AskUserQuestion to let Mike select which to build.
Common Mistakes
- Running serially instead of in parallel. The corpus is large; 3 parallel Explore agents cut wall time to ~1/3.
- Reading full chat logs. Only the first-user-message of each session is worth the tokens. Grep and sample.
- Forgetting to filter against installed skills. Without the filter, the output is 80% things Mike already has.
- Proposing too many candidates. Cap at 5-7. More than that paralyzes selection.
- Missing framework-prefixed skills in the installed-list.
dialed:*, peon-ping-*, superpowers:* count — include them in the filter.
- Not distinguishing "recurring" from "just happened recently". A pattern needs to span multiple sessions to be a real candidate.
Don't Re-Derive
If Mike has already run review-chats recently (check /Users/mikelady/dev/mike-skills/review-chats/last-run.md if present), start from that baseline rather than re-scanning the entire corpus. Ask Mike if he wants a delta from last run or a fresh full scan.
