SKILLEMALL.ai

BC hugo-blog-tool-free

面向个人博主的 Hugo 博客发布工具,简化文章发布流程。核心能力: - 自动分析文章内容,提取标题、标签、分类 - 生成符合 Hugo 规范的 Front Matter - 自动添加截断标记(more) - Git 推送发布到远程仓库 适用场景: - 个人技术博客文章发布 - Markdown 文章的 Front Matter 自动生成 - 博客内容的版本管理与推送 差异化: 免费版聚焦个人博主的单篇文章发布场景,提供自动化的 Front Matter 生成与推送流程,开箱即用

ClawHub Hermes author: 天轰穿 v1.0.2 MIT-0 2 files body ≈ 1 750 tokens Open the sourceclawhub.ai analyzed 2 d ago

面向个人博主的 Hugo 博客发布工具,简化文章发布流程。核心能力: - 自动分析文章内容,提取标题、标签、分类 - 生成符合 Hugo 规范的 Front Matter - 自动添加截断标记(more) - Git 推送发布到远程仓库 适用场景: - 个人技术博客文章发布 - Markdown 文章的 Front…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationKubernetesSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
62
Run on models
none yet
Process rating
C
51/100
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.
  2. 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 description-long-hermes description is 242 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • 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 51/100

  • 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. 4 mutating operations with no state check
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 30 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1750 tokens
  • low 13 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
  • -2localhost URLs: will not work for another user
  • +2Single-language instructions
  • +3Description length 242: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (15 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: suspicious
The skill is mostly a Hugo blog publishing helper, but it gives broad automatic write, read, commit, and push instructions without clear user confirmation.
LLM: suspicious (high) · 26 Jul 2026