SKILLEMALL.ai

AC web-data-monitor-claw

全网数据探测虾 — 监控竞品官网或特定站点的页面变动,自动巡查并在关键内容变化时发送通知。 适用场景:竞品价格监控、法规更新监控、招聘信息监控、新闻舆情监控、技术文档更新监控。 触发关键词:监控 爬虫 网页变动 竞品监控 价格监控 法规更新 舆情监控 数据采集 网站监控 页面变化 自动抓取 web-data-monitor Use when the user wants to: monitor a website for changes, track competitor prices, watch for regulatory updates, scrape web data periodically, or get notified when specific page content changes.

ClawHub Agent Skills author: Ricky v1.0.0 MIT-0 6 files · 1 script body ≈ 421 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
C
52/100
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

    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: 6. 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 52/100

    • 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
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 26 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 421 tokens
    • 100Running it twice. No mutating operations

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 358: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    This is a real website-change monitoring skill, but it needs Review because it also teaches anti-bot evasion, proxy/CAPTCHA handling, and cookie-based scraping beyond its stated public-page scope.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026