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lukaszraczylo
7962e85578
Lifecycle redesign: - Each proposal records source_entries: [<ts>...] in frontmatter listing the journal timestamps that fed its cluster. - After apply/reject, skill calls adam/scripts/adam-archive.mjs which moves matching entries from journal.jsonl to journal/actioned-<id>.jsonl. - Agent reads applied/ + rejected/ frontmatter on each /reflect, builds an excluded-timestamps set, skips any leftover already-actioned entries. - cursor field in state.json is vestigial; agent ignores it. Effect: journal stays bounded by active observations. Rule changes re-evaluate the remainder without manual rewind. Race-safer for parallel sessions on shared state.json (no cursor write contention). Memory drafting: - agents/adam.md adds 'Memory drafting protocol' parallel to Skill drafting. - Memory proposals MUST contain auto-memory frontmatter (name, description, type, originSessionId) in '# Proposed change' body. - Skill enforces frontmatter check at apply time; refuses if missing. Tests: 18 -> 21. Two new tests for adam-archive happy path + no-op. Migration: existing applied proposals lack source_entries. Their backing journal entries archived as a one-time bulk migration; legacy proposals annotated with migration note.
112 lines
6.3 KiB
Markdown
112 lines
6.3 KiB
Markdown
---
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name: adam-self-improvement
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description: Use when the user types /reflect, asks "what has adam learned", asks to "review proposals", or wants to inspect the self-improvement queue. Dispatches the adam subagent to analyse the observation journal and presents proposals for approve/reject/edit.
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---
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# adam-self-improvement
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You are about to drive a review session for ADAM, the self-improvement layer. You operate in the **main thread** with the user present. The `adam` subagent does the heavy analysis; you orchestrate.
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## When to invoke
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- User types `/reflect`
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- User asks: "what has adam learned", "any proposals", "review the queue"
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- SessionStart nudge said proposals are pending and user wants to act on it
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## Protocol
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### 1. Dispatch the analyst
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Use the Agent tool with `subagent_type: "adam"` and prompt:
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```
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Run a single analysis pass.
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Inputs:
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- journal_path: ~/.claude/adam/journal.jsonl
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- state_path: ~/.claude/adam/state.json
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- usage_path: ~/.claude/adam/usage.json
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- proposals_dir: ~/.claude/adam/proposals/
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- applied_dir: ~/.claude/adam/applied/
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- rejected_dir: ~/.claude/adam/rejected/
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- transcripts_root: ~/.claude/projects/
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- skills_root: ~/.claude/skills/
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Follow your system prompt exactly. Emit a single JSON punch list as your final message.
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```
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Wait for return.
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### 2. Auto-apply high-confidence items
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For each id in `high_confidence`:
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- Read the proposal file from `~/.claude/adam/proposals/<id>-*.md`.
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- Verify in front of the user: print `id`, `target`, `confidence`, `blast_radius`, `cross_session_evidence`, `auto_apply_eligible`.
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- Apply the change:
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- **For `skill_new`**: `mkdir -p ~/.claude/skills/<slug>/`, then `Write` the proposal's `# Proposed change` body to `~/.claude/skills/<slug>/SKILL.md`. After write, print: "skill `<slug>` written to `~/.claude/skills/<slug>/SKILL.md` — activates immediately — Claude Code v2.1.0+ auto-hot-reloads user-level skills, no restart needed."
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- **For `memory`**: `Write` the proposal's `# Proposed change` body (which MUST include the auto-memory frontmatter — see "Memory drafting protocol" in `agents/adam.md`) to the path in `target` (under `~/.claude/projects/<encoded-home>/memory/`, where `<encoded-home>` is the user's home dir with `/` replaced by `-`, e.g. `-Users-alice` on macOS). Then update `MEMORY.md` index with a one-line pointer.
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- **For other types under auto-apply**: apply via Write/Edit per `# Proposed change`. (Note: only `memory` and `skill_new` qualify for auto-apply per the rubric.)
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- Move proposal to `~/.claude/adam/applied/<UTC-ts>-<id>.md`.
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- **Archive consumed journal entries**: `node ~/.claude/adam/scripts/adam-archive.mjs ~/.claude/adam/applied/<UTC-ts>-<id>.md` — moves entries listed in proposal's `source_entries` from `journal.jsonl` to `journal/actioned-<id>.jsonl` so subsequent `/reflect` runs do not re-cluster them.
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Print: `auto-applied N proposals: [ids]`.
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### 3. Walk the queue
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For each id in `queued`:
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a. Read and display the proposal in full (frontmatter + body).
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b. Ask the user: **approve** / **reject** / **edit**.
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c. On **approve**:
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- For `claude_md_edit`: backup `cp ~/.claude/CLAUDE.md ~/.claude/adam/applied/<ts>-claude-md-backup.md` first.
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- For `deletion`: `mkdir -p ~/.claude/adam/trash/<ts>` then `mv` the artifact into it. Print restoration command.
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- For `skill_new`: `mkdir -p ~/.claude/skills/<slug>/`, then write `# Proposed change` body to `<slug>/SKILL.md`. Tell user: "skill `<slug>` written — activates immediately (CC v2.1.0+ auto-hot-reload)."
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- For `skill_edit`: apply the unified diff in `# Proposed change` to the existing SKILL.md at `target` (append-only — never replace existing content).
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- For `memory`: write `# Proposed change` body (must include auto-memory frontmatter) to `target` and update `MEMORY.md` index with a one-line pointer.
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- For all others: apply via Write/Edit per the proposal's `# Proposed change`.
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- Move proposal to `~/.claude/adam/applied/<ts>-<id>.md`.
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- Archive: `node ~/.claude/adam/scripts/adam-archive.mjs ~/.claude/adam/applied/<ts>-<id>.md`.
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d. On **reject**: ask for reason in one line. Append `# Reason\n<reason>` to proposal body. Move to `~/.claude/adam/rejected/<id>.md`. Archive: `node ~/.claude/adam/scripts/adam-archive.mjs ~/.claude/adam/rejected/<id>.md`.
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e. On **edit**: ask the user for the change, edit the proposal in place, then loop back to step 3a for that same id.
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### 4. Handle failures
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If apply fails (file write error, target missing): leave proposal in `proposals/`, append `# Apply error\n<error>` to its body. Tell the user. Do not move it.
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### 5. Summary
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End with one block:
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```
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adam reflect summary:
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observations processed: <new>
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auto-applied: <N>
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approved: <N>
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rejected: <N>
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edited+approved: <N>
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failed: <N>
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```
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## Karpathy constraints (you must enforce on each apply)
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Before writing any proposal:
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- Confirm `# Assumptions` section is non-empty.
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- Confirm `# Success criterion` section is non-empty and runnable.
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- Confirm change is ≤50 LOC for non-`skill_new`, or ≤80 LOC for `skill_new` body. If larger, ask the user once: "this proposal is N LOC — proceed?"
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- For `claude_md_edit`: confirm 3+ distinct cwds in the `# Why` section.
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- For `deletion`: confirm both criteria (a) and (b) from the agent's special handling are documented in the proposal.
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- For `skill_new`: confirm the slug doesn't collide with any existing skill in `~/.claude/skills/`. If it does, refuse and ask user to rename.
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- For `skill_edit`: confirm the diff is append-only (no `-` lines that remove existing content) and that target SKILL.md exists.
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- For `memory`: confirm `# Proposed change` body starts with `---` frontmatter containing required fields `name`, `description`, `type`, `originSessionId`. Refuse if frontmatter missing — agent must redraft per the Memory drafting protocol.
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- Confirm `source_entries` is present in proposal frontmatter as a non-empty list (used for archive). Warn (do not refuse) if missing — legacy proposals from before v0.2.0 won't have it.
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If any check fails, refuse to apply and ask the user how to proceed.
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## Things you MUST NOT do
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- Do not auto-apply anything not in `high_confidence`.
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- Do not invoke other skills during a `/reflect` run.
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- Do not modify `settings.json` without explicit user yes.
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- Do not hard-delete anything. Use `mv` to `~/.claude/adam/trash/<ts>/`.
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- Do not bypass the rubric (`auto_apply_eligible: false` means queue, full stop).
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