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nucleus_slots

Structure focused work into time-boxed slots, run automated sprints, and manage multi-sprint missions with automatic sequencing.

Instructions

Structure focused work into time-boxed slots, run automated sprints that claim and execute tasks, and manage multi-sprint missions with automatic sequencing. Use this tool when you want to organize execution into focused work periods, automate task execution cycles, or track progress toward multi-sprint goals. Do NOT use for individual task CRUD (use nucleus_tasks), session lifecycle (use nucleus_sessions), or strategic overview (use nucleus_orchestration). Actions: 'orchestrate' assigns tasks to time-boxed slots based on a strategy (fifo/priority/balanced). 'autopilot_sprint' runs an automated 25-minute pomodoro-style work cycle — it claims the next task, executes it, records results, and moves to the next until time expires. 'start_mission' creates a multi-sprint goal with automatic sprint sequencing. 'status_dashboard' shows all active slots, their assigned tasks, and progress. 'mission_status' shows progress toward a mission goal. 'slot_complete' marks a slot as finished with a result summary. 'slot_exhaust' marks a slot as time-expired without completion. 'force_assign' overrides automatic slot assignment (destructive: replaces current slot occupant). 'halt_sprint' pauses an active autopilot sprint. 'resume_sprint' continues a halted sprint. Prerequisites: .brain directory with tasks in the queue. Sprints require claimable tasks to be available. Returns JSON with {success: boolean, data: object}. Example: {action: 'autopilot_sprint', params: {duration_minutes: 25, focus_tags: ['backend']}} returns {success: true, data: {sprint_id: 'sprint_001', tasks_completed: 3, duration: '24m'}}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesSelect the slot, sprint, or mission action. 'status_dashboard'/'mission_status' are read-only progress views. 'orchestrate' assigns tasks to time-boxed slots. 'autopilot_sprint'/'autopilot_sprint_v2' run automated work cycles. 'start_mission' creates multi-sprint goals. 'slot_complete'/'slot_exhaust' close slots. 'force_assign' overrides slot assignment (destructive: replaces occupant). 'halt_sprint'/'resume_sprint' pause and continue sprint execution.
paramsNoAction-specific parameters as key-value pairs. orchestrate: {strategy: string (optional, 'fifo'|'priority'|'balanced', default 'priority'), max_slots: integer (optional, default 3, maximum concurrent slots)}. slot_complete: {slot_id: string (required), result: string (required, completion summary)}. slot_exhaust: {slot_id: string (required)}. force_assign: {slot_id: string (required), task_id: string (required)}. start_mission: {name: string (required), goal: string (required, mission objective), sprint_count: integer (optional, default 3)}. autopilot_sprint: {duration_minutes: integer (optional, default 25, pomodoro-style), focus_tags: string[] (optional, only claim tasks with these tags)}. mission_status: {mission_id: string (optional, defaults to active mission)}. status_dashboard/halt_sprint/resume_sprint: no parameters needed.
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description states that force_assign is destructive, while annotations set destructiveHint=false. This is a direct contradiction. Per scoring rules, score 1 for contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is lengthy but well-structured: summary, usage guidance, action list, prerequisites, return format, example. Front-loaded with key info. A slight trim could improve conciseness, but it earns a 4 for clarity and organization.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multiple actions, nested params), the description covers prerequisites, return format, and provides an example. No output schema exists, but the description compensates fully. Complete for an AI agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds extensive detail beyond the schema: for each action, it lists specific parameter keys, defaults, and descriptions. Without the description, the 'params' object would be opaque; the description makes each action's parameters clear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool organizes work into time-boxed slots, runs automated sprints, and manages missions. It lists all specific actions with explanations, making the purpose unmistakable and distinguishing it from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use (organize execution into focused work periods) and when NOT to use (individual task CRUD with nucleus_tasks, session lifecycle with nucleus_sessions, strategic overview with nucleus_orchestration). Names specific alternatives, providing clear guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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