SKILLEMALL.ai

BC code-dev-pipeline

八人协作代码开发流水线,用于复杂代码开发任务。**必须使用此 skill 当用户要求开发代码、写程序、实现功能,或对代码质量有要求时**。特别适合: - 复杂功能开发(>50行代码、多文件、需要测试) - 需要UI/前端设计的项目(HTML/CSS/JS、React/Vue等) - 对代码质量有要求的任务(需要审查、测试、文档) - 关键/策略性代码(需要多人把关) - 用户不想中间确认、只想看最终结果 **八人角色**:Coordinator(协调员)、Analyst(需求分析)、Architect(架构设计)、UIDesigner(UI设计)、Coder(代码编写)、Reviewer(代码审查)、Tester(测试验证)、Validator(最终验收)。 **三种模式**:完整模式(全流程)、快速模式(精简流程)、维护模式(紧急修复)。 触发词:开发代码、写程序、实现功能、代码流水线、复杂开发、需要测试的代码、前端开发、UI设计、网页开发

ClawHub Agent Skills author: clawaizhang v1.0.0 MIT-0 11 files body ≈ 1 630 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

ProcedureSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
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: 11. 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. 106 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1630 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
  • -217 emoji in the instructions: noise for the model
  • -48 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 430: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 106 items
  • +4Has examples (9 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This appears to be a coding workflow skill, but it gives itself broad control over ordinary coding requests and repository changes without enough user-directed scoping.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026