SKILLEMALL.ai

BC cron-assist

定时助手是定时调度专家的\"自然语言层\"。用户说\"每天早上9点发日报\",它解析意图、匹配模板、产出调度命令并执行,全程无需懂 cron。Use when 需要文本翻译、多语言转换、本地化处理时使用。不适用于专业医学法律翻译认证。适用于独立开发者、企业团队和自动化工作流场景。支持中文交互,无需复杂配置即开即用。

ClawHub Hermes author: 天轰穿 v1.0.1 MIT-0 2 files body ≈ 3 087 tokens Open the sourceclawhub.ai analyzed 3 d ago

定时助手是定时调度专家的\"自然语言层\"。用户说\"每天早上9点发日报\",它解析意图、匹配模板、产出调度命令并执行,全程无需懂 cron。Use when 需要文本翻译、多语言转换、本地化处理时使用。不适用于专业医学法律翻译认证。适用于独立开发者、企业团队和自动化工作流场景。支持中文交互,无需复杂配置即开即用。

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationData and analyticstype 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
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Unexpected scalar at node end at line 8, column 76: …供标准化流程和配置参考. 该工具经过差异化增强,结合实际使用痛点进行了优化."。"自然语言驱动的定时任务助手,内置模板库与成本优化,把口语意图秒变可靠调度.… ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-long-hermes description is 158 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "pricing_tier"

Process rating: all ten parameters 56/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 56 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3087 tokens
  • low 26 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
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 158: enough signal without eating the budget
  • +4Structure: 55 headings
  • +3Step-by-step instructions: 56 items
  • +4Has examples (25 code blocks)
  • +1License stated

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

External checks

ClawHub: suspicious
This scheduling skill is mostly about cron task management, but its broad unrelated activation text and persistent task mutation commands need review before installation.
LLM: suspicious (high) · 8 Aug 2026