Track and surface sub-agent dispatch calibration ratios. Extract from JSONL transcript or read existing ledger. Per-agent clean/blocked/errored/partial trends.
日本語の概要は準備中です。原文の説明を表示しています。
Configure or reconfigure aigent-OS identity, priorities, authority, projects, people, and decision logic
日本語の概要は準備中です。原文の説明を表示しています。
実行スコア 未検証
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
/start owns the day-one onboarding arc. /setup is the deeper configuration flow and may also be used later to revise one section.
Read .aigent/state.json first.
ready, route through /start unless the operator explicitly requested advanced setup.ready, ask which configuration area needs revision rather than replaying the entire interview.Before writing, set status: setup-in-progress while preserving any prior completedAt. On interruption, the next /start or /setup should resume from the last durably completed section.
Ask one question at a time and write each completed section immediately.
Ask for the operator's role, responsibilities, preferred collaboration style, and risk posture. Update system/00_identity.md without replacing framework-owned doctrine.
Ask for the top two or three active priorities, the most urgent outcome, operating mode, and blockers. Update vault/memory/ACTIVE_PRIORITIES.md.
Ask what the AI may handle autonomously, what needs confirmation, what is human-only, and whether spending has an escalation threshold. Update system/12_authority_matrix.md.
Ask what makes the operator accept or reject opportunities, their active-work limit, and their most common time trap. Update system/14_decision_framework.md.
For each active project, capture purpose, current state, priority, next action, and relevant people. Create or update notes under vault/projects/ and vault/people/, then connect them from active priorities with wikilinks.
Ask whether any specialized agents are useful now. For each accepted agent, capture name, scope, tools, model tier, escalation boundary, and success criteria. Store the definition in vault/agents/ with valid name: and tools: frontmatter so the installer can register it in .claude/agents/.
After all requested sections are durably written:
vault/memory/SESSION_LOG.md..aigent/state.json to:{
"schemaVersion": 1,
"status": "ready",
"completedAt": "<ISO-8601 timestamp>"
}
.aigent/first-run-done for compatibility with older installs./open, normal work, and /close.Do not mark the installation ready when required writes failed.
まだレビューはありません。使ってみた感想をお寄せください。
ログインなしで書き込めます。使ってみた感想、質問、動かなかった環境などを気軽にどうぞ。
まだコメントはありません。最初のコメントを書いてみませんか。
Track and surface sub-agent dispatch calibration ratios. Extract from JSONL transcript or read existing ledger. Per-agent clean/blocked/errored/partial trends.
日本語の概要は準備中です。原文の説明を表示しています。
Compose the AIgent's body state by reading existing signals. Lazy compute. Never polled. Reports the five pressures + recommended reflex.
日本語の概要は準備中です。原文の説明を表示しています。
Generate a structured delegation brief for any task
日本語の概要は準備中です。原文の説明を表示しています。
Quarterly skill that walks the skill-index against the actual SKILL.md files on disk, reports drift (skills indexed that no longer exist, skills on disk that aren't enrolled, skills whose descriptions have changed since enrollment). Hardens the auto-enrollment pipeline against silent rot.
日本語の概要は準備中です。原文の説明を表示しています。
When a [CADDY] hint fires and the principal is confused why, /caddy-explain walks the scoring transparently — which trigger matched, what points it earned, what the threshold was, what other skills were close. Pairs with the legibility thesis. Caddy's decisions should be inspectable on demand.
日本語の概要は準備中です。原文の説明を表示しています。
Enroll a skill into Caddy's index so it can be surfaced when the right prompt arrives. Use when a new skill is created, copied in, or when a skill needs updated triggers. Usage — "/caddy-enroll <path to SKILL.md>".
日本語の概要は準備中です。原文の説明を表示しています。