brain-ingest-gate
Pre-write quality gate for content entering the brain. No raw copies: a bare cp/mv into the brain repo is a bug. Before any new page lands, resolve named…
Task lifecycle management with stable task IDs. Add, complete, defer, remove, and review tasks with deterministic action routing and fail-closed ambiguity handling. Maintains a running task list as a brain page.
$ npx -y skills add garrytan/gbrain --skill daily-task-manager --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/daily-task-managerContext preview
The summary Claude sees to decide when to auto-load this skill.
Task lifecycle management with stable task IDs. Add, complete, defer, remove, and review tasks with deterministic action routing and fail-closed ambiguity handling. Maintains a running task list as a brain page.
name: daily-task-manager version: 2.0.0 description: | Task lifecycle management with stable task IDs. Add, complete, defer, remove, and review tasks with deterministic action routing and fail-closed ambiguity handling. Maintains a running task list as a brain page. triggers: - "add task" - "complete task" - "what are my tasks" - "task list" - "defer task" tools: - search - get_page - put_page - add_timeline_entry mutating: true upstream: daily-task-manager@fc834ee
This skill guarantees:
After every action, report a structured result so callers (including sub-agents) can chain reliably:
{action, task_id, status: ok|not_found|ambiguous|needs_confirmation, priority, date, page: "ops/tasks.md", saved: true|false}For `review`, return the grouped active-task list instead of a single task_id. When invoked with the trigger "task list json", return a JSON array of task objects `{id, description, priority, due, status}` instead of markdown.
Use ONLY the declared tools. `get_page("ops/tasks.md")` to read, `put_page("ops/tasks.md", …)` to write, `add_timeline_entry` for the audit trail, `search` for cross-referencing. Do not shell out to `gbrain` CLI verbs from this skill; the tools are the interface. (When the user runs this manually outside an agent, the CLI equivalents are `gbrain get ops/tasks` / `gbrain put ops/tasks` — equivalents only, not the skill's interface.)
Map user intent deterministically before touching state:
1. **Load.** `get_page("ops/tasks.md")`. **First run:** if the page does not exist, create it from the Output Format template, then proceed. 2. **Validate.** Determine the action via Action Routing. If required fields are missing (see per-action rules), ask ONE concise clarification before mutating state. Never fabricate priorities, due dates, or defer reasons. 3. **Identify the target task** (complete/defer/remove): match by `id` when given; otherwise fuzzy-match description against ACTIVE tasks only. Zero matches → return `not_found`, do not mutate. Multiple matches → list candidates with IDs, return `ambiguous`, do not mutate. 4. **Execute:**
5. **Save.** `put_page("ops/tasks.md")` after any mutation. Diff-mindset: touch only the affected lines; preserve all other content, including sections this skill doesn't recognize.
Each task carries a stable ID so later actions can target it safely:
# Tasks
## P0 — Urgent
- [ ] <!-- id: t-20260115-01 --> {task description} (due: {date})
## P1 — Today
- [ ] <!-- id: {task-id} --> {task description} (due: {date optional})
## P2 — This Week
- [ ] <!-- id: {task-id} --> {task description} (due: {date optional})
## P3 — Backlog
- [ ] <!-- id: {task-id} --> {task description}
## Deferred
- [ ] <!-- id: {task-id} --> {task descriptioGive the agent you already use a memory you control. GBrain stores explicit facts with their sources, supports corrections and withdrawal, and makes the same memory available across your agents.
Repo: garrytan/gbrain
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