SKILLEMALL.ai

BC product-design-workflow

完整的产品设计全流程(含每日定时任务+汇报机制): 1. 每日定时生成3个产品idea(按市场行情/A股/基金主题,1个小白向+2个普通向) 2. 生成PRD产品设计文档 3. 制作HTML原型页面 4. 上传到服务器 5. 分步骤汇报到指定群 【需要用户提供的参数】: - 服务器配置:server-host, server-user, server-pass, server-path, preview-domain - 汇报群ID:target-group-id - 每日定时时间:schedule-time(默认08:50开始) 使用场景:快速产品设计、产品创意头脑风暴、原型制作发布、每日产品提案生成

ClawHub Agent Skills author: hoovaycn v1.1.1 MIT-0 22 files body ≈ 914 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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
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: 22. 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. 36 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 914 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
  • -219 emoji in the instructions: noise for the model
  • -32 of 4 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 307: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 36 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (6 of 7)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This skill does what it advertises, but it handles server credentials and report destinations in ways that need human review before use.
LLM: suspicious (high) · VirusTotal: · 29 May 2026