Files
lukaszraczylo 78bf0f1e1e Initial commit: ADAM self-improvement layer for Claude Code
- 8 friction signals via lightweight hook (correction, retry_loop, weak_agent,
  tool_error_loop, dead_end, edit_churn, build_loop, subagent_dispatch_pattern)
- Deterministic confidence rubric with cross-session evidence gate
- /reflect skill to dispatch the analyst subagent and walk the queue
- Skill overlap detection (prefer skill_edit over skill_new on collision)
- Solution synthesis from transcript context for new skill drafts
- Soft-delete trash, never hard rm
- 18 tests covering all signals
2026-05-10 02:32:13 +01:00

5.2 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 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.

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 to target and update MEMORY.md index.
  • For all others: apply via Write/Edit per the proposal's # Proposed change.
  • Move proposal to ~/.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. 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.

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).