SKILLEMALL.ai

BC scrape-web-tool-free

网页抓取工具免费版为个人用户提供轻量级的网页内容抓取与提取能力. 核心能力: - 网页纯文本抓取 - CSS选择器精准提取 - 抓取结果保存文件 - 多种输出格式 适用场景: - 单页内容快速提取 - 文章正文抓取归档 - 数据字段精准提取 差异化:免费版聚焦核心抓取与选择器提取流程,基于Scrapling实现轻量部署,适合个人用户快速抓取网页内容,无需复杂配置. 适用关键词: 网页抓取, scrape, 爬虫, CSS选择器, 内容提取, Scrapling, Python

ClawHub Hermes author: 天轰穿 v1.0.1 MIT-0 2 files body ≈ 1 735 tokens Open the sourceclawhub.ai analyzed 3 d ago

网页抓取工具免费版为个人用户提供轻量级的网页内容抓取与提取能力.

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

IntegrationSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
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.
  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 240 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 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. Tools declared in frontmatter
  • 100Steps. 18 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1735 tokens
  • 100Running it twice. No mutating operations
  • low 12 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 240: enough signal without eating the budget
  • +4Structure: 43 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (12 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
This web-scraping skill is mostly purpose-aligned, but its trigger wording and file-writing behavior are too broad and underspecified for automatic installation.
LLM: suspicious (medium) · 26 Jul 2026