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nucleus_agents

Destructive

Manage agent lifecycles, spawn specialized sub-agents, run automated code review and repair, orchestrate agent swarms, search persistent memory, and ingest tasks from external sources.

Instructions

Manage multi-agent lifecycles including spawning specialized sub-agents, running automated code review and repair, orchestrating agent swarms for complex tasks, searching persistent memory, ingesting tasks from external sources, and viewing real-time dashboards. Use this tool when you need to create new agents, review or fix code, coordinate parallel work, or query the knowledge base. Do NOT use for individual task CRUD (use nucleus_tasks), session management (use nucleus_sessions), or cross-brain sync (use nucleus_federation). Actions: 'spawn_agent' creates a sub-agent with a specific role (reviewer/implementer/researcher) and goal (side effect: may start a new process). 'critique_code' runs automated code review on a file, returning issues and suggestions. 'fix_code' attempts automated repair of a described issue in a file. 'apply_critique' applies review feedback. 'orchestrate_swarm' coordinates multiple agents working on a complex task in parallel. 'search_memory' queries the persistent engram store by keyword (read-only). 'read_memory' retrieves a specific engram by key. 'ingest_tasks' imports tasks from external sources like GitHub issues, CSV, or JSONL files (side effect: creates tasks). 'rollback_ingestion' undoes a previous import (destructive: deletes imported tasks). 'ingestion_stats' shows import history. 'dashboard' shows live system metrics including agent count, task throughput, and memory usage. 'snapshot_dashboard'/'list_dashboard_snapshots' manage dashboard snapshots. 'get_alerts'/'set_alert_threshold' configure monitoring alerts. 'respond_to_consent'/'list_pending_consents' handle human-in-the-loop approval flows for sensitive operations. Prerequisites: .brain directory. Returns JSON with {success: boolean, data: object}. Example: {action: 'search_memory', params: {query: 'authentication', limit: 5}} returns {success: true, data: {results: [{key: 'engram_x', content: 'Auth uses JWT...', score: 0.95}]}}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesSelect the agent management action. 'search_memory'/'read_memory'/'dashboard'/'get_alerts'/'ingestion_stats'/'list_pending_consents'/'session_briefing'/'list_dashboard_snapshots' are read-only. 'spawn_agent' creates a new sub-agent. 'critique_code'/'fix_code'/'apply_critique' handle automated code review and repair. 'orchestrate_swarm' coordinates parallel agents. 'ingest_tasks' imports from external sources. 'rollback_ingestion' is destructive (deletes imported tasks). 'set_alert_threshold' configures monitoring. 'respond_to_consent' approves/denies sensitive operations.
paramsNoAction-specific parameters as key-value pairs. spawn_agent: {role: string (required, 'reviewer'|'implementer'|'researcher'|'planner'), goal: string (required, what the agent should accomplish), tools: string[] (optional, tool names to grant access to)}. critique_code: {file_path: string (required, path to file to review), diff: string (optional, specific diff to focus review on)}. fix_code: {file_path: string (required), issue: string (required, description of the problem to fix)}. search_memory: {query: string (required, search term), limit: integer (optional, default 10)}. read_memory: {key: string (required, engram key)}. ingest_tasks: {source: string (required, 'github'|'csv'|'jsonl'), file_path: string (required, path to source file)}. set_alert_threshold: {metric: string (required, metric name), threshold: number (required), operator: string (optional, 'gt'|'lt'|'eq', default 'gt')}. handoff_task: {task_id: string (required), to_agent: string (required), context: object (optional)}. respond_to_consent: {consent_id: string (required), approved: boolean (required)}. rollback_ingestion/ingestion_stats/dashboard/snapshot_dashboard/list_dashboard_snapshots/get_alerts/list_pending_consents/session_briefing/register_session/apply_critique/orchestrate_swarm: no parameters needed.
Behavior5/5

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

Discloses side effects for spawn_agent ('may start a new process') and ingest_tasks ('creates tasks'), destructive nature of rollback_ingestion ('deletes imported tasks'), read-only status of several actions, prerequisites ('.brain directory'), and return format (JSON with success and data). This adds value beyond annotations by providing specific behavioral details.

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 thorough and well-organized, with a clear front-load of purpose and usage, followed by detailed action breakdowns. While every sentence adds value, the length could be slightly reduced by grouping similar actions; however, the structure is logical and easy to follow.

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 complexity of the tool (20 actions, no output schema), the description is fully comprehensive: includes prerequisites, return format, example, side effects, and explicit mentions of destructive/read-only behaviors. No gaps remain for correct invocation.

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?

Adds extensive meaning beyond the schema: describes required fields, optional fields, allowed values (e.g., role enum), defaults, and provides an example usage. Covers all 20 actions with specific parameter structures, fully compensating for the schema's generic parameter description.

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 manages multi-agent lifecycles with specific verbs and resources (spawn, critique, fix, orchestrate, search, ingest, etc.) and explicitly distinguishes from sibling tools like nucleus_tasks, nucleus_sessions, and nucleus_federation.

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?

Provides explicit when-to-use ('when you need to create new agents, review or fix code, coordinate parallel work, or query the knowledge base') and when-not-to-use with named alternatives ('Do NOT use for individual task CRUD (use nucleus_tasks), session management (use nucleus_sessions), or cross-brain sync (use nucleus_federation)').

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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