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.

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Repository: yaojingang/yao-geo-skills
Last source activity: July 19, 2026 at 10:58
Detected SKILL.md language: English
Stars: 730
Forks: 145

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.

A direct command skips the review prompt. Inspect the source before running it.

npx skills add https://github.com/yaojingang/yao-geo-skills --skill yao-deepseek-crawler

The command stays on one line. Scroll horizontally to inspect it before copying.

Prefer a local copy? Download the files currently available to SkillsMP.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

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SKILL.md

Source instructions · Read-only preview

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yao-chatgpt-crawler

Use when a user provides ChatGPT web AI-search keywords, repeat count, target entity, entity type, OpenCLI profile, and crawl interval preference, then needs repeated crawls aggregated into JSON plus a Kami HTML GEO report. Not for generic crawling, ChatGPT API chat, SEO writing, or one-off answers.

2026-07-20

yao-doubao-crawler

Use when a user needs repeated Doubao AI-search collection from web or Android Appium into compatible JSON plus Markdown/Excel/HTML GEO reports. Requires keywords/questions and repeat count; target entity/type are required only for target-vs-competitor diagnosis. Not for generic scraping, Doubao API chat, hidden API extraction, SEO writing, high-frequency automation, or one-off answers.

2026-07-16

yao-geoflow-cli

Use when operating an existing GEOFlow 2.1+ system from CLI, API v1, or authenticated admin web for catalog/material/task/job/article operations, enterprise knowledge, growth-center leads, distribution, analytics, URL import, theme editor, frontend-capability sync, system updates, settings, tokens, users, or preflight. Do not use for implementation, schema changes, direct DB edits, frontend design, or invented API routes.

2026-07-05

View all from this repository

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.