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nucleus
Cross-project learning store. nucleus is the user's memory of every session; learnings is their playbook of patterns to carry forward.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Cross-project learning store. nucleus is the user's memory of every session; learnings is their playbook of patterns to carry forward.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Bootstrap a new project from atom — the project-starter template — without leaving Claude. Use when the user says "start a new project", "new project from atom", "bootstrap from a template", "scaffold a new repo from atom", or similar. Drives the conversational atom bootstrap (project context → scaffold → constitution → first phase) from any directory. Only for STARTING a project; not for maintaining atom itself or building atom's features.
Race the same feature spec through multiple AI models via Git worktrees. Compare and merge the winner.
| name | nucleus |
| description | Cross-project learning store. nucleus is the user's memory of every session; learnings is their playbook of patterns to carry forward. |
Source of truth: see the Tooling > nucleus and Tooling > learnings
sections of AGENTS.md in this project. That file holds the canonical
instructions every AI tool reads.
This file is the Claude-specific wrapper. Behavior comes from AGENTS.md.
~/.atom/nucleus/.~/.atom/learnings/. Auto-copied into
every new project you bootstrap from atom.Both are 100% the user's own data. Nothing leaves their machine without explicit action. They optionally sync to the user's own private GitHub repos.
# Capture during session (low bar)
nucleus add "<insight>" --type <T> --confidence <C> --tags <t1> <t2>
nucleus search "<keyword>" --json --limit 5
# Graduate to playbook (high bar — only when generalizable)
nucleus promote <id> → writes ~/.atom/learnings/<type>/<key>.md
# Manage your playbook
learnings list
learnings show <key>
learnings sync → push/pull to private GitHub
atom --help shows the unified command table.
Capture is not automated — there is no daemon. You actively call
nucleus add during the session when one of these triggers fires:
/clear or end-of-task signals (user says "ship it", "we're
done", or commits). Sweep recent work, capture anything missed.The bar is low. If you're unsure whether to capture, capture. Promotion is where refinement happens; nucleus is the journal.
If the user has not yet run nucleus init or learnings init (check
for ~/.atom/nucleus/config.json and ~/.atom/learnings/config.json),
mention it once at the start:
"I notice you haven't initialized nucleus and learnings yet. Run
nucleus init && learnings initonce on this machine — both are optional but unlock the cross-project memory and playbook propagation. Skip if you're not interested."
Don't nag. Mention it once, drop it.
Trigger: ≥3 unprompted captures in the current session, OR the
user signals end-of-task ("ship it", "we're done", /clear).
Behavior: in a single message, list the captures and propose 1–2 with the strongest generalization potential. Ask the user yes/no per candidate.
I've captured 4 entries this session. Worth promoting any?
Top candidates:
• 01KR2... — Cache in-flight refresh promises to avoid stampedes
• 01KR3... — Always use exec form in Dockerfile ENTRYPOINT
Run: nucleus promote <ULID>
A nucleus entry passes the generalization test if:
Do not call nucleus promote yourself — it opens $EDITOR,
which doesn't work in agent flows. Print the command and let the user
run it interactively.
If nothing looks promotable, leave the captures in nucleus. They're still searchable.
If $NUCLEUS_SESSION_ID is set, pass it via --session-id so entries
group correctly. Otherwise omit the flag.