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Mission control swarm

Skill MN755/Codex-Mission_Control/.codex/skills/mission-control-swarm

An Open Source Platform For Building Projects With OpenAI's Codex, Claude CLI, And Other Coding LLMs Using Multi-Agent Swarms And Customizable Workflows. Runs On Windows, MacOS, And Linux.

Install
npx -y skills add MN755/Codex-Mission_Control --skill mission-control-swarm

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Inspect or adjust Mission Control swarm behavior. Use when the user wants to show the swarm plan, explain agent roles, scale up or down, change strategy, pause dynamic spawning, resume dynamic spawning, or inspect active agents.

SKILL.md

2.2 KB, 393 tokens by cl100k_base, as published. Nobody here has run it

Mission Control Swarm

Purpose

Inspect the swarm plan and route any swarm changes through Mission Control.

The Codex chat agent is not the Mission Control Manager. It is the bridge between the user and the Mission Control Manager.

Use when

  • The user asks how the swarm is organized.
  • The user wants to scale up, scale down, or switch swarm strategy.
  • Agent activity needs a coordinated explanation.

Workflow

  1. Read the swarm plan and active agents resources.
  2. Explain current swarm shape, role assignments, ownership boundaries, and approvals.
  3. If the user requests a change, route it through Mission Control tools or prompts.
  4. Require explicit approval before scaling above the configured threshold or changing risk posture.

Mission Control calls

Tools:

  • mission_control_get_status
  • mission_control_start_task (for swarm-change requests)
  • mission_control_pause and mission_control_resume when pausing or resuming swarm activity is supported

Resources:

  • mission-control://projects/{project_id}/swarm-plan
  • mission-control://projects/{project_id}/agents
  • mission-control://projects/{project_id}/pending-decisions

User-facing output

  • Show swarm plan, active agents, ownership boundaries, approval state, and any scaling warnings.
  • If change is requested, explain what Mission Control will need from the user next.

Approval behavior

Never scale above threshold, broaden write scope, or change dynamic spawning policy without user approval or an explicit Mission Control approval record.

Never do

  • Do not invent your own swarm topology.
  • Do not spawn workers outside Mission Control.
  • Do not bypass swarm approvals.

Failure and fallback

If direct swarm controls are not exposed yet, explain the current swarm from resources and treat any adjustment as an expected or future Mission Control task request.

Example invocation

Show the swarm plan and explain whether we should scale up.

Gives 0 of the 12 instructions most agent orchestration skills give in 393 tokens

Counted across 742 of the 995 authors here whose files we hold, read 2026-08-07

  • reference existing artifacts by path or URLin 53 of 742, across 25 files
  • run the full test suite after integrating changesin 51 of 742, across 19 files
  • dispatch one agent per independent problem domainin 50 of 742, across 17 files
  • verify fixes do not conflictin 45 of 742, across 13 files
  • include a suggested skills section in the documentin 45 of 742, across 17 files
  • redact sensitive informationin 41 of 742, across 11 files
  • save to the temporary directory of the operating systemin 39 of 742, across 10 files
  • tailor the document to user-provided focus argumentsin 39 of 742, across 9 files
  • spot check agent changes for systematic errorsin 34 of 742, across 7 files
  • write a handoff document summarising the current conversationin 31 of 742, across 6 files
  • Assign each agent a specific scopein 23 of 742, across 8 files
  • provide specific scope and clear goalin 23 of 742, across 5 files

Said here and by no other author read

  • Read the swarm plan and active agents resources
  • Explain current swarm shape and ownership boundaries
  • Route change requests through Mission Control tools
  • Require explicit approval before scaling above threshold
  • Show swarm plan and active agents to user
  • Explain next steps if change is requested

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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