SKILLEMALL.ai

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通过引导式提问完善内部黑客松、创新赛、培训作品和内部流程优化项目的想法,再将其交付为可运行、可演示、可部署、可验收的最小产品。适用于内部工具、业务原型、管理后台、轻量 B/S 系统、小程序、数据采集和自动化程序,以及补齐后端、持久化、部署说明、演示脚本或验收闭环。不用于单纯生图、纯文案/PPT 或与完整交付无关的局部代码修改。

ClawHub Agent Skills author: tan v0.1.1 MIT-0 3 files body ≈ 618 tokens Open the sourceclawhub.ai analyzed 3 d ago

通过引导式提问完善内部黑客松、创新赛、培训作品和内部流程优化项目的想法,再将其交付为可运行、可演示、可部署、可验收的最小产品。适用于内部工具、业务原型、管理后台、轻量 B/S 系统、小程序、数据采集和自动化程序,以及补齐后端、持久化、部署说明、演示脚本或验收闭环。不用于单纯生图、纯文案/PPT…

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

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
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: 3. 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 "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"

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. 39 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 618 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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 164: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 39 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: clean
This is a coherent Chinese-language MVP delivery skill that asks for confirmation before development and does not contain hidden execution, exfiltration, or persistence mechanisms.
LLM: benign (high) · VirusTotal: · 4 Sept 2026