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AC taobao-mcp-benchmark

淘宝桌面版MCP工具评测框架。用于系统化测试MCP工具的各项功能，生成专业的技术评测报告。Use when 需要对淘宝MCP工具进行评测、测试、验收、迭代验证。

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 9 files · 2 scripts body ≈ 2 954 tokens Open the sourcegithub.com↗ analyzed 2 d ago

淘宝桌面版MCP工具评测框架。用于系统化测试MCP工具的各项功能，生成专业的技术评测报告。Use when 需要对淘宝MCP工具进行评测、测试、验收、迭代验证。

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWordAI and agentsCommercetype 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    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: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 51/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 145 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2954 tokens
    • low 12 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 80: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -224 emoji in the instructions: noise for the model
    • -32 of 3 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Structure: 49 headings
    • +3Step-by-step instructions: 145 items
    • +4Has examples (17 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.