Files
claude-adam/skills/adam-self-improvement/SKILL.md
T
lukaszraczylo 7962e85578 v0.2.0: drop cursor, add source_entries lifecycle, mandate memory frontmatter
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.
2026-05-10 04:29:49 +01:00

6.3 KiB

name, description
name description
adam-self-improvement 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.

adam-self-improvement

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.

When to invoke

  • User types /reflect
  • User asks: "what has adam learned", "any proposals", "review the queue"
  • SessionStart nudge said proposals are pending and user wants to act on it

Protocol

1. Dispatch the analyst

Use the Agent tool with subagent_type: "adam" and prompt:

Run a single analysis pass.

Inputs:
- journal_path: ~/.claude/adam/journal.jsonl
- state_path: ~/.claude/adam/state.json
- usage_path: ~/.claude/adam/usage.json
- proposals_dir: ~/.claude/adam/proposals/
- applied_dir: ~/.claude/adam/applied/
- rejected_dir: ~/.claude/adam/rejected/
- transcripts_root: ~/.claude/projects/
- skills_root: ~/.claude/skills/

Follow your system prompt exactly. Emit a single JSON punch list as your final message.

Wait for return.

2. Auto-apply high-confidence items

For each id in high_confidence:

  • Read the proposal file from ~/.claude/adam/proposals/<id>-*.md.
  • Verify in front of the user: print id, target, confidence, blast_radius, cross_session_evidence, auto_apply_eligible.
  • Apply the change:
    • 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."
    • 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.
    • 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.)
  • Move proposal to ~/.claude/adam/applied/<UTC-ts>-<id>.md.
  • 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.

Print: auto-applied N proposals: [ids].

3. Walk the queue

For each id in queued:

a. Read and display the proposal in full (frontmatter + body). b. Ask the user: approve / reject / edit. c. On approve:

  • For claude_md_edit: backup cp ~/.claude/CLAUDE.md ~/.claude/adam/applied/<ts>-claude-md-backup.md first.
  • For deletion: mkdir -p ~/.claude/adam/trash/<ts> then mv the artifact into it. Print restoration command.
  • 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)."
  • For skill_edit: apply the unified diff in # Proposed change to the existing SKILL.md at target (append-only — never replace existing content).
  • For memory: write # Proposed change body (must include auto-memory frontmatter) to target and update MEMORY.md index with a one-line pointer.
  • For all others: apply via Write/Edit per the proposal's # Proposed change.
  • Move proposal to ~/.claude/adam/applied/<ts>-<id>.md.
  • Archive: node ~/.claude/adam/scripts/adam-archive.mjs ~/.claude/adam/applied/<ts>-<id>.md. 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. e. On edit: ask the user for the change, edit the proposal in place, then loop back to step 3a for that same id.

4. Handle failures

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.

5. Summary

End with one block:

adam reflect summary:
  observations processed: <new>
  auto-applied: <N>
  approved: <N>
  rejected: <N>
  edited+approved: <N>
  failed: <N>

Karpathy constraints (you must enforce on each apply)

Before writing any proposal:

  • Confirm # Assumptions section is non-empty.
  • Confirm # Success criterion section is non-empty and runnable.
  • 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?"
  • For claude_md_edit: confirm 3+ distinct cwds in the # Why section.
  • For deletion: confirm both criteria (a) and (b) from the agent's special handling are documented in the proposal.
  • 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.
  • For skill_edit: confirm the diff is append-only (no - lines that remove existing content) and that target SKILL.md exists.
  • 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.
  • 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.

If any check fails, refuse to apply and ask the user how to proceed.

Things you MUST NOT do

  • Do not auto-apply anything not in high_confidence.
  • Do not invoke other skills during a /reflect run.
  • Do not modify settings.json without explicit user yes.
  • Do not hard-delete anything. Use mv to ~/.claude/adam/trash/<ts>/.
  • Do not bypass the rubric (auto_apply_eligible: false means queue, full stop).