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Boot the session, load context from the vault, and surface what matters

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wrg32786/aigent-os星标 25(GitHub 25 + cccskills 0)

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包含的文件(1)

  • SKILL.md3.9 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Session Open

Deprecated. This skill is superseded by [[skills/resume/SKILL.md|/resume]] (docs/two-verb-lifecycle.md). New installs should reach for /resume; this file stays for anyone still invoking /open by habit during the transition.

Run this at the start of every normal working session.

Nightly alert surface

Before normal orientation, run the local watchdog with the same configured time zone and cutoff used by the pass:

node daemons/nightly-watchdog.mjs --root <aigent-root>

Surface every active named alert from vault/memory/runtime/NIGHTLY_ALERTS.jsonl. The append-only ledger and stderr are the default delivery channels; no external coordination service is required. If the ledger is unreadable, report ALERT_LEDGER_INVALID and continue the resume path. An alert-read failure must never suppress session orientation or make the hook indistinguishable from "not installed."

First-run detection

Before the normal protocol, read .aigent/state.json.

  • If status is not ready, run /start instead of the normal open protocol.
  • If the JSON state is missing but .aigent/first-run-done exists, treat the installation as ready and create the JSON state as a compatibility migration.
  • Do not inspect natural-language placeholders in system/00_identity.md. Product state belongs in machine-readable state, not in whether a sentence happens to survive an edit.

Protocol

Unbanked-session recovery: Compare .aigent/last-close, if present, with the newest Session Captures in vault/daily/. If newer captures exist, recover a short summary into vault/memory/SESSION_LOG.md, mark it (auto-recovered), and continue. State the recovery in one neutral line.

  1. Load the heat index from vault/memory/HEAT_INDEX.json when present. Use hot_top_20 as the prioritized reading list. If missing, use steps 2 through 6 normally.
  2. Read the latest daily note in vault/daily/.
  3. Read the session log at vault/memory/SESSION_LOG.md and extract the newest next action and open threads.
  4. Read active priorities at vault/memory/ACTIVE_PRIORITIES.md.
  5. Follow the graph from the latest daily note and open threads into the three to five most relevant project, concept, person, or agent notes.
  6. Check delegation at vault/memory/DELEGATION_TRACKER.md for blocked, stale, or review-ready work.
  7. Decision aging: compare vault/memory/DECISION_LOG.md and vault/memory/DECISION_OUTCOMES.md. Surface at most three unresolved decisions around 30, 60, or 90 days old.
  8. Attention reconciliation: compare the last seven days in vault/daily/ with intended focus in vault/memory/ACTIVE_PRIORITIES.md. Surface material drift only.
  9. Skill gap scan: once per week, inspect memory/SKILL_GAPS.md. If an open gap is older than seven days, run /skill-hunt on the oldest one and update the ledger if resolved.
  10. Compute runtime state:
python3 "$AIGENT_ROOT/daemons/runtime/update-active-state.py"
  1. Read runtime state at vault/memory/runtime/ACTIVE_STATE.json. Use next_valid_action, blocked_items, active reflexes, and mode to orient the session.
  2. Reconcile weekly: on Monday or after seven days without a reconciliation, run /reconcile and surface contradictions only.

Output

Give a brief greeting, then surface only:

  • Due decision-aging prompts.
  • Material attention drift.
  • Stale or blocked items.
  • Work dropped from the previous next action.
  • Open threads requiring attention now.

If nothing needs flagging, greet the operator and let them drive. Do not dump a full priority report merely because the files exist.

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