Yao deepseek crawler

Skill ShenyuanNext/wepr-growth-skills/skills/yao-deepseek-crawler

Use when a user provides DeepSeek web AI-search keywords, repeat count, target entity, and entity type, then needs repeated fresh-window crawls aggregated into JSON plus a Kami HTML GEO report. Not for generic website crawling, DeepSeek API chat, SEO writing, or one-off answer generation.From its SKILL.md

Install

npx -y skills add ShenyuanNext/wepr-growth-skills --skill yao-deepseek-crawler

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One thing to look at

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SKILL.md

2.4 KB, 468 tokens by cl100k_base, as published. Nobody here has run it

Yao DeepSeek Crawler

Inputs

Standard inputs: keywords/questions, repeat count, target entity, entity type (人/person, 公司/company, 产品/product), browser profile, and optional output directory. Competitors must match the target type. Reports default to Simplified Chinese with an English summary toggle.

Workflow

Read references/user-setup-and-usage.md for install, prerequisites, and user-facing steps.
Read references/deepseek-crawl-workflow.md for crawler setup, preflight, delay, resume, and batch rules.
Read references/report-contract.md for JSON schema, metrics, target/competitor recognition, and report rules.
Run node scripts/preflight.mjs --profile <profile> before fresh crawling.
Stage 1: run scripts/deepseek_batch_crawl.mjs with questions, repeat, profile, target entity/type, --safe-random-delay, and output dir.
Stage 2: run scripts/analyze_deepseek_results.py on any crawl JSON with target entity/type, optional brands file, report output dir, and semantic review mode. Use --semantic-review auto by default; use --semantic-review required for formal delivery when AI review must pass.
Return the raw crawl JSON, structured Markdown, structured Excel workbook, HTML report, summary JSON, semantic-review cache when present, and failed logs. Reports include AI semantic labels for entity recognition, target-vs-best-3 radar, click-to-reveal bubbles, Chinese source names, clickable citations, title intent, compact treemap, and GEO actions.

Honest Boundaries

Do not use for generic website crawling, DeepSeek API chat, SEO copywriting, or one-off answer generation.
Reuses local DeepSeek web automation; does not bypass login, CAPTCHA, bot checks, or hidden data.
Probability metrics are repeated-sample estimates, not ground truth.
Inferred competitors are heuristic unless --semantic-review required passes. AI semantic review is an audit enhancement and never replaces hard-rule gates or answer-body evidence.
Review aliases, semantic labels, excluded candidates, and competitor tables before external use.
Preserve raw answers, reference titles, URLs, and logs.