AC frontend-arch-analyzer
This skill should be used when the user needs to analyze frontend project architecture evaluate tech stack choices review component design patterns assess build configuration check monorepo structure audit VSCode extension setup or review OpenHarmony project layout. It generates structured architecture evaluation reports with scores grades strengths weaknesses and actionable refactoring suggestions. Trigger phrases include "analyze architecture" "review frontend project" "tech stack evaluation" "component design review" "build config audit" "monorepo analysis" "前端架构分析" "技术栈评估" "组件设计评审" "工程化诊断" "构建配置审计" "项目体检".
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 52/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (frontend-arch-analyzer) differs from the folder (eno)
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 38 steps
- 100Execution cost. Instruction body is 1629 tokens
- low 10 top-level sections: this looks like several domains in one skill
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
- -217 emoji in the instructions: noise for the model
- +2Single-language instructions
- +5Description quotes 9 example trigger phrases
- +3Description length 617: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (4 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.