- name
- prompt-ab-lab
- description
- Design, log, compare, and score prompt experiments so users can systematically
- version
- 1.1.0
- metadata
- openclaw
- requires
- bins
- emoji
- 🧰
Prompt A/B Lab
Purpose
Design, log, compare, and score prompt experiments so users can systematically improve outputs instead of guessing.
Trigger phrases
- 比较两个提示词
- prompt ab test
- 提示词实验
- 哪个 prompt 更好
- 建一个评测表
Ask for these inputs
- prompt A and B
- task
- evaluation criteria
- test set
- weights if any
Workflow
- Define what success looks like before comparing prompts.
- Generate an evaluation rubric and structured test table.
- Log outputs per test case and compute weighted scores.
- Summarize tradeoffs instead of declaring a winner too early.
- Recommend the next experiment iteration.
Output contract
- experiment plan
- scored comparison table
- rubric
- next-iteration suggestions
Files in this skill
- Script:
{baseDir}/scripts/prompt_experiment_logger.py - Resource:
{baseDir}/resources/eval_rubric.md
Operating rules
- Be concrete and action-oriented.
- Prefer preview / draft / simulation mode before destructive changes.
- If information is missing, ask only for the minimum needed to proceed.
- Never fabricate metrics, legal certainty, receipts, credentials, or evidence.
- Keep assumptions explicit.
Suggested prompts
- 比较两个提示词
- prompt ab test
- 提示词实验
Use of script and resources
Use the bundled script when it helps the user produce a structured file, manifest, CSV, or first-pass draft. Use the resource file as the default schema, checklist, or preset when the user does not provide one.
Boundaries
- This skill supports planning, structuring, and first-pass artifacts.
- It should not claim that files were modified, messages were sent, or legal/financial decisions were finalized unless the user actually performed those actions.
Compatibility notes
- Directory-based AgentSkills/OpenClaw skill.
- Runtime dependency declared through
metadata.openclaw.requires. - Helper script is local and auditable:
scripts/prompt_experiment_logger.py. - Bundled resource is local and referenced by the instructions:
resources/eval_rubric.md.