self-improve

# Self-Improve

Review the current conversation, or the project's past sessions when asked, to extract durable lessons and route each one to the right knowledge layer.

## Step 1: Detect Context

Available destinations:

- **Project CLAUDE.md / AGENTS.md** — The root `.claude/CLAUDE.md` (may be a symlink to `../AGENTS.md` — resolve it), plus any nested `CLAUDE.md` / `AGENTS.md` files in subdirectories. Claude Code loads a subdirectory's file on demand when files in that subtree are accessed, so a lesson scoped to one subtree belongs in the nearest enclosing file, with the root reserved for project-wide rules.
- **Auto memory** — The project-specific memory directory named by the active harness. An effective `autoMemoryDirectory` setting overrides its location; otherwise it normally lives at `<Claude config home>/projects/<encoded project root>/memory/`, where the config home is `CLAUDE_CONFIG_DIR` when set and `~/.claude` otherwise. The key replaces every character outside `A-Za-z0-9` with `-`, and long keys may be truncated and hashed, so prefer the exact harness-provided path over recomputing it. List the directory and read `MEMORY.md` if it exists.
- **Skills** — Project skills at `skills/` or `.claude/skills/` (resolve symlinks)

Discover the project CLAUDE.md/AGENTS.md files (the root file and any nested ones in subdirectories) and read them, then read MEMORY.md. When those files point at a knowledge base the repo maintains, read its index too; it is a documentation source for Step 3 rather than a routing destination. List all skill directories but do not read them yet — Step 2 needs to run first so you know what to look for.

### Turbo Skill Detection

If `~/.turbo/repo/` exists, identify which installed skills are turbo skills:

- List directories in `~/.turbo/repo/claude/skills/`
- Any skill in `~/.claude/skills/` that has a matching directory in `~/.turbo/repo/claude/skills/` is a turbo skill
- Skills only in `~/.claude/skills/` (no match in the repo) are user/project skills

**Verification rule (mandatory before routing in Step 4):** For every candidate skill that is about to be routed as turbo, confirm with a fresh `test -d ~/.turbo/repo/claude/skills/<name>` check that the skill actually lives in the turbo repo. Do not rely on remembered listings from earlier in the session, filename hits in grep output, or assumptions based on where a SKILL.md was read from. A miss here mislabels a user/project skill as turbo, triggers the contribution flow unnecessarily, and can introduce session-specific content into a shared skill — so the check is not optional.

**Exception:** If the current project IS the turbo repo (i.e., the working directory contains this skill collection), route turbo skill lessons through the **Existing user/project skill** destination in Step 4 — edits go directly to `claude/skills/<name>/` in the project, with no installed-copy indirection and no contribution flow.

## Step 2: Gather Session Evidence and Scan for Lessons

### Recover Pre-Compaction Evidence

**Skip** when the conversation is visible in full from the user's own first message.

When it starts from a summary of earlier work instead, recover the compacted turns from the on-disk transcript. Spawn a single subagent (`model: "opus"`, no `name`). Wait for it to report before continuing; do not relaunch it if it has not yet reported. The subagent's prompt must include:

1. The absolute path of the project root
2. A distinctive phrase from the visible conversation, for confirming which transcript belongs to this session
3. An instruction to read [references/transcript-miner.md](references/transcript-miner.md) for transcript location, extraction, and output format

Treat the returned items as raw evidence for the scan below.

### Sweep Past Sessions

**Run** when asked to distill sessions beyond the current one. **Skip** otherwise.

Propose a cutoff first: take the newest modification time in the memory directory from Step 1, state it, then use `AskUserQuestion` to confirm sweeping from it or sweeping the whole history. A memory file's timestamp records a write rather than a completed sweep, so it bounds the work without settling what a previous run covered. When the directory is absent or empty, sweep the whole history without asking.

Spawn a single subagent (`model: "opus"`, no `name`). Wait for it to report before continuing; do not relaunch it if it has not yet reported. The subagent's prompt must include:

1. The absolute path of the project root
2. The confirmed cutoff as an ISO-8601 timestamp, or that there is none
3. An instruction to read [references/transcript-miner.md](references/transcript-miner.md) and follow its sweep process

Treat the returned items as raw evidence for the scan below.

### Identify Session Skills

Before scanning for lessons, identify which skills were loaded during this session:

- Scan the conversation for Skill tool invocations and SKILL.md reads from `~/.claude/skills/`
- Build a list of session skills, marking each as turbo or user/project skill (using the detection from Step 1)
- This list informs routing in Step 4: when a lesson clearly arose from a specific skill's workflow, that skill is the natural routing target

### Scan for Lessons

Scan the full conversation with this priority:

1. **Corrections** — Where the user interrupted, said "no", "actually", "stop", "not like that", redirected, or manually fixed something Claude did wrong. Highest-value lessons.
2. **Repeated guidance** — Instructions the user gave more than once. Across separate sessions this counts even where each instance reads as ordinary steering on its own.
3. **Skill-shaped knowledge** — Domain expertise that was needed repeatedly, tool/API integration details that had to be looked up, decision frameworks that emerged for evaluating options, content templates or writing conventions that were refined, and multi-step workflows where ordering mattered (as reusable domain knowledge, not the workflo