How do I install the Yao Deepseek Crawler skill?

Run npx skillmds@latest add yaojingang/yao-deepseek-crawler in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Yao Deepseek Crawler safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Yao Deepseek Crawler?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Yao Deepseek Crawler free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Yao Deepseek Crawler?

yaojingang (@yaojingang) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Yao Deepseek Crawler by yaojingang — Agent Skill

Name: Yao Deepseek Crawler
Author: yaojingang

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.

yaojingang 325b12a 112 files · 3.7 MB Updated Sep 17, 2026

File contents

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.

---name: yao-deepseek-crawlerdescription: 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.---# Yao DeepSeek Crawler## InputsStandard 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.## Workflow1. Read `references/user-setup-and-usage.md` for install, prerequisites, and user-facing steps.2. Read `references/deepseek-crawl-workflow.md` for crawler setup, preflight, delay, resume, and batch rules.3. Read `references/report-contract.md` for JSON schema, metrics, target/competitor recognition, and report rules.4. Run `node scripts/preflight.mjs --profile <profile>` before fresh crawling.5. Stage 1: run `scripts/deepseek_batch_crawl.mjs` with questions, repeat, profile, target entity/type, `--safe-random-delay`, and output dir.6. 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.7. 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.

Frequently asked questions