Parallel launch
Skill OutlineDriven/odin-claude-plugin/skills/parallel-launch
Use when the request has multiple independent sub-tasks, cross-domain research, or parallelizable file or module work.From its SKILL.md
npx -y skills add OutlineDriven/odin-claude-plugin --skill parallel-launchAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
2.1 KB, 389 tokens by cl100k_base, as published. Nobody here has run it
Parallel Launch
Decompose the given task into independent agent groups and execute them in broad parallel.
Process
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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 for parallelism decisions.
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Design agent groups for each independent concern:
- Assign a clear, scoped objective (one concern per agent).
- Select the appropriate tailored agent type (Explore, Plan, or a domain specialist) — prefer a task-specific agent over a general one.
- Define expected output format so results can be composed.
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Launch all independent agents in a single tool call.
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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.
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Review composed output by dispatching 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.
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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.
- If the task has fewer than 2 independent concerns, execute directly instead of launching agents.
What ships with it: 1 file
1.3 KB alongside SKILL.md
references/
- delegation-scenarios.md1.3 KB
Gives 0 of the 12 instructions most product growth skills give in 389 tokens
Counted across 728 of the 1,010 authors here whose files we hold, read 2026-08-07
- Read product marketing context before asking questionsin 24 of 728, across 18 files
- Define the ideal customer profilein 21 of 728, across 3 files
- Document a rollback plan before deploymentin 21 of 728, across 12 files
- Analyze the codebase to understand the productin 19 of 728, across 1 file
- Ask clarifying questions about the value propositionin 19 of 728, across 1 file
- Search for companies matching the criteriain 19 of 728, across 1 file
- Look for signals of immediate needin 19 of 728, across 1 file
- Assign a fit score from one to tenin 19 of 728, across 1 file
- Identify the target decision-maker rolein 19 of 728, across 1 file
- Suggest a personalized contact strategyin 19 of 728, across 1 file
- Provide conversation starters for outreachin 19 of 728, across 1 file
- Format results in a scannable markdown templatein 19 of 728, across 1 file
Said here and by no other author read
- decompose the task into independent concurrent concerns
- sequence dependent batches after independent batches complete
- assign one scoped concern per agent
- prefer a task-specific agent over a general one
- define expected output formats for all agents
- launch all independent agents in a single call
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.