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AC fe-cli

前端项目脚手架 CLI。支持 React/Vue/Next.js/Nuxt.js/Astro/React Native + shadcn/Ant Design/MUI/Tailwind + Zustand/Redux + i18n，初始化标准化前端项目。支持 9 种项目类型：Web SPA、后台管理、移动 H5、 Electron 桌面端、Tauri 桌面端、SSR (Next.js/Nuxt)、小程序 (微信/Taro)、React Native 移动端、 静态建站 (Astro/Gatsby/VitePress)。 触发：用户要求创建新前端项目、初始化项目、搭建脚手架， 或提到"新建前端项目"、"初始化项目"、"脚手架"、"创建 React/Vue 项目"。 也可用于检查/审查已有前端项目的规范性。

ClawHub Agent Skills author: zZihan v3.1.1 MIT-0 14 files body ≈ 2 523 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmentAI and agentsInfrastructuretype 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
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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: 5. 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 "homepage"

Process rating: all ten parameters 50/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
  • 100Steps. 44 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2523 tokens
  • 100Progress reporting. Reports progress

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 2 example trigger phrases
  • +3Description length 356: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 44 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: suspicious
This frontend scaffolding skill is not malicious, but it ships several powerful or privacy-sensitive defaults that users should review before generated projects are used beyond local experimentation.
LLM: suspicious (high) · 24 May 2026