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AC amazon-scraper

High-performance containerized web scraper (Docker + Crawlee + Playwright). Use when user mentions any of these: 爬虫, 爬取, 抓取, 采集, 数据采集, 爬数据, 抓数据, 获取数据, scrape, crawl, extract, fetch data, pull data, 亚马逊, Amazon, ASIN, BSR, Best Sellers, 畅销榜, 热销榜, 新品榜, 飙升榜, 排行榜, 选品, 竞品分析, 竞品调研, 市场调研, 品类分析, 类目分析, 产品调研, 月销量, bought in past month, 销量, 评论数, 价格对比, YouTube, 视频字幕, 转录, transcript, 网页内容, 网站数据, 页面抓取, 动态页面, TikTok, Twitter, X, 社交媒体数据, 帖子内容, 关键词搜索, 搜索结果, search results, 产品详情, 产品信息, listing数据, listing分析, top 100, top sellers, 热门产品, 爆款, 跑量款, 价格带, 评分分布, review分析, 评论分析

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files body ≈ 991 tokens Open the sourcegithub.com↗ analyzed 2 d ago

High-performance containerized web scraper (Docker + Crawlee + Playwright).

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

AnalyzerDockerYouTubePlaywrightMedia and videoInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
97
Quality 40%
84
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

    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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Dangerous commands cmd-privilege assets/amazon_handler.js:24
      Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
      launchContext: { launchOptions: { headless: true, args: ['--no-sandbox', '--disable-setuid-sandbox'] } },
      detectorcode literal
    • low Dangerous commands cmd-privilege assets/main_handler.js:23
      Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
      args: ['--no-sandbox', '--disable-setuid-sandbox'], // Required for Docker
      detectorcode literal
    • low Dangerous commands cmd-privilege assets/youtube_handler.js:10
      Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
      args: ['--no-sandbox', '--disable-setuid-sandbox'],
      detectorcode literal

    Files scanned: 5. 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 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. No external tools needed
    • 100Steps. 21 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 991 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 557: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.