SKILLEMALL.ai

AC brand-kit

企业品牌视觉资产端到端生成。能力:①需求分析(BA1)②设计生成(BA2,Logo+形态派生+SVG批量+信息注入+小尺寸优化)③格式转换(BA3,SVG→PNG+ICO+校验)④整合交付(BA4,HTML+完整性+清理)⑤品牌规范与扩展应用(BA5-BA6,可选)。全量87个文件(2 HTML + 33 SVG + 51 PNG + 1 ICO)。33 SVG = 3核心标志 + 18 VI系统 + 3品牌规范 + 9扩展应用。6域25种任务。触发词:生成品牌资产、VI系统、Logo套件、商标稿件、名片信封信纸、favicon全套、brand asset、meta-skill-system。

ClawHub Agent Skills author: 波动几何 v1.0.0 MIT-0 13 files body ≈ 1 957 tokens Open the sourceclawhub.ai analyzed 3 d ago

企业品牌视觉资产端到端生成。能力:①需求分析(BA1)②设计生成(BA2,Logo+形态派生+SVG批量+信息注入+小尺寸优化)③格式转换(BA3,SVG→PNG+ICO+校验)④整合交付(BA4,HTML+完整性+清理)⑤品牌规范与扩展应用(BA5-BA6,可选)。全量87个文件(2 HTML + 33 SVG…

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

ProcedureMarketingDesignInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
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: 13. 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. 79 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1957 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 300: enough signal without eating the budget
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 79 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: clean
This skill is a disclosed brand-asset generator that runs local rendering scripts and handles business contact details for expected deliverables, with some cleanup-command caution for users.
LLM: benign (high) · VirusTotal: · 28 Jun 2026