outlinedriven/parallel-launch
skills/parallel-launch/SKILL.md
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.
$ install --global
skillsauthnpx skillsauth add outlinedriven/odin-codex-plugin parallel-launchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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TrivyContainer and dependency vulnerability scanner
95%
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SemgrepStatic code analysis for vulnerabilities
95%
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mcp-scan (Snyk)Model Context Protocol security validation
95%
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Snyk (dep)Open source security scanning
50%
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Socket.devSupply chain security analysis
50%
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Last scanned: Apr 27, 2026, 9:18 AM237.1s2 files scanned
SKILL.md
- name:
- parallel-launch
- description:
- 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.
Parallel Launch
Decompose the given task into independent agent groups and execute them in broad parallel.
Process
-
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.
-
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.
-
Launch all independent agents in a single tool call — never sequentially when parallel is possible.
-
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.
-
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.
-
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.
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