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AF ab-test-agent-workflow

多agent双盲 A/B 测试工作流。对多个 AI model/Agent 进行多轮次、双盲对照测试。 核心role：coordinate者（Coordinator）、受测者 A/B（Contestant）、评测者（Judge）。 trigger场景："A/B 测试"、"双盲测试"、"比较 AI model"、"model评测"、"测试工作流"、 "compare models"、"blind test"、"multi-round evaluation"。

ClawHub Agent Skills author: JohnSmithfan v1.1.0-en2 MIT-0 2 files body ≈ 1 504 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 40/100 · Will not run — References files that are not bundled: scripts/anonymizer.py

ProcedureAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
F
40/100
Will not run
References files that are not bundled: scripts/anonymizer.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/anonymizer.py

Process rating: all ten parameters 40/100

Will not run. References files that are not bundled: scripts/anonymizer.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/anonymizer.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 28 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1504 tokens
  • 100Running it twice. No mutating operations
  • low 10 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 6 example trigger phrases
  • +3Description length 230: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (18 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

External checks

ClawHub: clean
This skill is a disclosed A/B testing workflow for comparing AI agents and does not show hidden or disproportionate behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026