AD ab-test-agent-workflow
多智能体双盲 A/B 测试工作流。对多个 AI 模型/Agent 进行多轮次、双盲对照测试。 核心角色：协调者（Coordinator）、受测者 A/B（Contestant）、评测者（Judge）。 触发场景："A/B 测试"、"双盲测试"、"比较 AI 模型"、"模型评测"、"测试工作流"、 "compare models"、"blind test"、"multi-round evaluation"。
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 46/100
- 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
- 40Consistency. Frontmatter name (ab-test-agent-workflow) differs from the folder (ab-test-agent-workflow-1-1-0)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 28 steps
- 100Execution cost. Instruction body is 1357 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 5 example trigger phrases
- +3Description length 204: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 28 items
- +4Has examples (18 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.
External checks
ClawHub: clean
This is a coherent A/B testing workflow skill, with a notable blind-test integrity flaw but no evidence of malicious behavior or hidden data access.
LLM: benign (high) · VirusTotal: · 29 May 2026