seed-protocol-design

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SOP: design random seed strategy for reproducibility

yogsoth-ai By yogsoth-ai schedule Updated 6/16/2026

name: seed-protocol-design description: 'SOP: design random seed strategy for reproducibility' version: 1.0.0 category: experiment-execution type: sop execution: subagent prompt: ./prompt.md input: Experiment design + list of randomness sources + repetition requirements output: Seed allocation strategy + seed value table + reproducibility guarantee plan dependencies: sops: - spawn-agent

SOP: Seed Protocol Design

Design random seed strategy to ensure experiment reproducibility while quantifying variance from randomness through multi-seed runs.

Execution

Subagent — spawned via subagent-spawning/spawn-agent skill.

Why Subagent

Seed strategy requires identifying all randomness sources in the system (initialization, data sampling, dropout, etc.) and designing a consistent seed propagation scheme — demands deep understanding of system architecture.

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOP When to use
spawn-agent Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent.
Install via CLI
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill seed-protocol-design
Repository Details
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