SKILLEMALL.ai

BD api-probe

专业的 API 接口测试与验证工具。支持 REST API、GraphQL、WebSocket 测试,自动生成测试用例,验证接口契约,模拟 Mock 服务。当用户需要测试 API 接口、验证接口参数、测试接口性能、生成接口测试报告、Mock 接口数据、或进行接口契约测试时使用此技能。也适用于用户提到"接口测试"、"API测试"、"REST测试"、"接口验证"、"Mock服务"、"契约测试"、"Postman"、"Swagger"、"OpenAPI"等场景。

ClawHub Agent Skills author: ShyLamb-token v1.0.0 MIT-0 2 files body ≈ 5 164 tokens Open the sourceclawhub.ai analyzed 3 d ago

专业的 API 接口测试与验证工具。支持 REST API、GraphQL、WebSocket 测试,自动生成测试用例,验证接口契约,模拟 Mock 服务。当用户需要测试 API 接口、验证接口参数、测试接口性能、生成接口测试报告、Mock…

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmentData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
D
44/100
Unfinished process
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5164 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 44/100

  • 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
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5164 tokens
  • 100Steps. 12 steps
  • 100Consistency. Name and required fields are in place
  • 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

  • +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 230: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 12 items
  • +4Has examples (9 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
The skill is a coherent API testing helper, but it can generate or run mutating, load, and security tests against user-supplied APIs without strong upfront safeguards.
LLM: suspicious (high) · VirusTotal: · 28 Jul 2026