SKILLEMALL.ai

AC pans-gpu-solution-builder

GPU 算力方案构建器。根据客户的工作负载类型(训练/推理/微调/批量推理/开发测试)、 部署规模(小型/中型/大型/企业级)和月度预算,自动推荐最优 GPU 配置 (H100/A100/L40S/A10G/RTX 4090 等),生成含 GPU 型号、数量、算力、 月度/小时成本的配置表、扩展路线图和技术建议,输出 Markdown 或 JSON 格式。 触发词:GPU方案, 算力配置, 方案构建, GPU推荐, 配置推荐, solution builder, GPU选型, 算力方案

ClawHub Agent Skills author: dashiming v1.0.0 MIT-0 3 files body ≈ 272 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
C
53/100
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

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

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 4 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 272 tokens
  • 100Running it twice. No mutating operations

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 245: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 4 items
  • +4Has examples (1 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This skill is a disclosed Ziniao Browser automation bridge skill that uses a local API key and browser-control tools for its stated purpose.
LLM: benign (medium) · VirusTotal: · 29 May 2026