SKILLEMALL.ai

AC timer-alert-tool-free

定时提醒工具(免费版)面向个人用户与独立开发者,提供后台定时器与到时提醒能力:支持多种时间格式(秒/分/时/分秒/时分秒)、自定义提醒文案、番茄钟工作法、多计时器并行与后台进程管理。定时器在后台运行,完成后触发系统通知。Use when 需要生成营销文案、写作内容、标题优化、内容创作时使用。不适用于纯技术文档撰写.

ClawHub Hermes author: 天轰穿 v1.0.1 MIT-0 2 files body ≈ 1 518 tokens Open the sourceclawhub.ai analyzed 2 d ago

定时提醒工具(免费版)面向个人用户与独立开发者,提供后台定时器与到时提醒能力:支持多种时间格式(秒/分/时/分秒/时分秒)、自定义提醒文案、番茄钟工作法、多计时器并行与后台进程管理。定时器在后台运行,完成后触发系统通知。Use when 需要生成营销文案、写作内容、标题优化、内容创作时使用。不适用于纯技术文档撰写.

As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
55/100
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. 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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • 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 "edition"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 55/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1518 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • low 11 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

  • +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
  • +2Single-language instructions
  • +3Description length 158: enough signal without eating the budget
  • +4Structure: 43 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (9 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
This timer skill mostly describes a normal local reminder tool, but it also asks to be used for unrelated writing and marketing tasks while requiring command execution and background process control.
LLM: suspicious (high) · 26 Jul 2026