SKILLEMALL.ai

AD yotta-skill-creator

元造 —— 从内嵌模板一键生成合规技能目录并做结构自检:命名校验(yotta- 前缀 / 小写连字符 / 元X 规范 / 目标不重复)+ 完整发布件脚手架(SKILL.md / README 中英四方式安装 / package.json / CHANGELOG / LICENSE / NOTICE / install.sh + bin/install.js / .gitignore / .npmignore / publish.yml / references / assets)+ 占位符替换 + 结构自检;--self-use 自用模式只生成技能本体(SKILL.md / references / 可选 CLI),不生成任何发布件。触发:新建一个 yotta- 技能、从零搭技能脚手架、想把发布规范里的坑固化成模板时;或用户说 元造 / 造技能 / 脚手架 / scaffold / 新建技能 等。边界(Do NOT trigger):不替用户写技能正文与脚本逻辑(SKILL.md 正文 / scripts 需人工开发);不做发布前校验与三源发布(那是元守 yotta-publish-guard);不做既有技能目录的批量改造。

ClawHub Agent Skills author: YottaMeta v0.1.1 MIT-0 26 files · 1 script body ≈ 869 tokens Open the sourceclawhub.ai analyzed 4 d ago

元造 —— 从内嵌模板一键生成合规技能目录并做结构自检:命名校验(yotta- 前缀 / 小写连字符 / 元X 规范 / 目标不重复)+ 完整发布件脚手架(SKILL.md / README 中英四方式安装 / package.json / CHANGELOG / LICENSE / NOTICE /…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
D
43/100
Unfinished process
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

    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: 14. 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 43/100

    • 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
    • 30Running it twice. 9 mutating operations with no state check
    • 60Tools and files. Uses tools (git, python) that frontmatter does not declare
    • 100Steps. 24 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 869 tokens

    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
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 520: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 24 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    The skill is mainly a scaffold generator, but its bundled installers can persist the skill into many agents' skill directories without confirmation.
    LLM: suspicious (high) · 3 Sept 2026