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SKILL verified Apache-2.0 Self-run

Parallel Launch

skill-outlinedriven-odin-codex-plugin-parallel-launch · by OutlineDriven

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.

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Install

$ agentstack add skill-outlinedriven-odin-codex-plugin-parallel-launch

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

✓ Security review passed
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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.