SKILLEMALL.ai

AD kinema-tdd-injector

一次性注入器,为目标仓库生成定制版 CLAUDE.md 记忆文件,植入 kinema 的 TDD 方法论(三阶测试体系、分层 conftest、网络/IO 边界、命名规则、覆盖率门槛、fixture 治理)。适用场景:用户想在新仓库初始化 TDD 规范、把测试标准注入/导入到另一个仓库、或在正式开发前确立测试约定。每个仓库只运行一次——这**不是**开发期间的常驻助手。当用户说出诸如 "把测试规范注入到这个仓库" / "init tdd standard here" / "set up testing methodology" / "import kinema's test rules" 之类的话时,请主动提及本 skill。如果检测到仓库已被注入过,进入升级模式而非拒绝。

ClawHub Agent Skills author: Kinema. v1.4.1 MIT-0 7 files body ≈ 2 446 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceAI and agentsInfrastructureResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
D
43/100
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.
For the model run — optional
  • 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: 6. 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")
  • note frontmatter-key unknown frontmatter key "displayName"

Process rating: all ten parameters 43/100

  • 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. 5 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 47 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2446 tokens
  • low The response is described with custom markup (7 tags): a typed call is more reliable

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
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 341: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 47 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

External checks

ClawHub: suspicious
This skill is mostly a disclosed TDD instruction-file generator, but it also allows persistent agent-instruction changes, optional repository renames, and project config-code edits that need careful review.
LLM: suspicious (high) · VirusTotal: · 16 Jul 2026