# Reproducibility Protocol

> Ensure experiment reproducibility through systematic environment and seed control

- Skill: `yogsoth-ai/reproducibility-protocol` (Agent Skill)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/reproducibility-protocol`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/reproducibility-protocol/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/reproducibility-protocol

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# Tactic: Reproducibility Protocol

## Orchestration Pattern

1. **Assess Reproducibility Requirements** → Determine level needed (exact, statistical, conceptual)
2. **seed-protocol-design** → Design random seed strategy for all stochastic components
3. **environment-specification** → Lock all software, hardware, and configuration dependencies
4. **Define Verification Plan** → How to confirm reproducibility (re-run subset, cross-machine test)
5. **Document Non-Determinism** → Identify and document unavoidable sources of variance

## Decision Criteria

| Reproducibility Level | Requirement | When to Use |
|----------------------|-------------|-------------|
| Exact (bit-for-bit) | Same hardware + deterministic ops | Debugging, verification |
| Statistical (within CI) | Same distribution of results | Standard research |
| Conceptual (same conclusion) | Same qualitative findings | Cross-platform validation |

## Quality Checks

- Are all random seeds documented and controllable?
- Is the full software environment captured (versions, dependencies)?
- Are hardware-specific non-determinisms identified (GPU atomics, cuDNN)?
- Is there a verification protocol (re-run N times, check variance)?
- Are data preprocessing steps deterministic or seeded?
- Is the order of data loading controlled?
- Are model initialization seeds separate from data shuffling seeds?
- Is there a plan for cross-machine reproducibility testing?

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## Available SOPs

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

| SOP | When to use |
| --- | --- |
| environment-specification | SOP: define complete experiment environment specification |
| seed-protocol-design | SOP: design random seed strategy for reproducibility |

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