outlinedriven/odin-codex-plugin

parallel-launch

Decompose a task into independent concerns and execute them through broadly parallel, specialized agent groups. Use when a request involves multiple independent sub-tasks, research across separate domains, or work that can be parallelized across files or modules.

First seen Jun 4, 2026

Installation

$ npx skills add outlinedriven/odin-codex-plugin --skill parallel-launch

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 15
License LICENSE
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,700 B
  • docs SUMMARY.md 286 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Parallel Launch

Decompose the given task into independent agent groups and execute them in broad parallel.

Process

  1. Analyze the task and identify independent concerns that can run concurrently.

- Each concern must be self-contained: no shared mutable state, no ordering dependency. - If concerns have dependencies, sequence the dependent batch after the independent batch completes. - Consult [delegation scenarios](./references/delegation-scenarios.md) for parallelism decisions.

  1. Design agent groups — for each independent concern:

- Assign a clear, scoped objective (one concern per agent). - Select the appropriate agent type (Explore, Plan, general-purpose, or domain specialist). - Define expected output format so results can be composed.

  1. Launch all independent agents in a single tool call — never sequentially when parallel is possible.
  1. Compose results once all agents complete:

- Merge non-conflicting outputs directly. - For conflicting or overlapping results, reconcile and present trade-offs to the user. - If any agent failed or returned incomplete results, report the gap and propose a targeted follow-up.

  1. Review composed output — dispatch a review agent to verify:

- Completeness: All original concerns addressed, no gaps. - Consistency: No contradictions between agent outputs. - Accuracy: Claims are substantiated, sources checked, no hallucinated findings. - Scope: Nothing extra built beyond what was asked. - For implementation work, additionally verify spec compliance and code quality.

  1. Report to user only after review passes.

Constraints

  • Agents per batch: match the number of truly independent concerns (avoid artificial splitting).
  • Each agent prompt must include full context — agents do not share memory.
  • Do not launch agents for trivially sequential work (single file, single concern).
  • If the task has fewer than 2 independent concerns, execute directly instead of launching agents.

Red Flags

  • Never skip review. Composed output must always pass through a review agent before reporting.
  • Never accept unverified composed output. If agents return conflicting results, the review agent must flag them — not silently pick one.
  • Never report to user before review passes. The review step is mandatory, not advisory.