REPOGEO REPORT · LITE

RUC-NLPIR/WebThinker

Default branch main · commit db387eb3 · scanned 6/30/2026, 1:28:01 PM

GitHub: 1,458 stars · 141 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface RUC-NLPIR/WebThinker, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Reposition README's opening to clearly state purpose and recency

Why:

CURRENT

The README excerpt shows the H1, followed by badges/links, then a 'Latest News' section, delaying the core value proposition.

COPY-PASTE FIX

Immediately after the H1, add a concise, problem-solution statement: 'WebThinker is a cutting-edge framework, accepted at NeurIPS 2025, that empowers large language models with deep web research and complex reasoning capabilities. It functions as a unified agent for diverse web-based problem-solving, enabling comprehensive information retrieval and detailed report generation, unlike older text analysis systems.'

mediumtopics#2

Refine GitHub topics for better categorization

Why:

CURRENT

deepresearch, deepsearch, deepseek-r1, gaia, gpqa, hle, o1, o3, qwq, reasoning, reportgen, research, webwalker

COPY-PASTE FIX

llm-agent, ai-agents, web-research, deep-reasoning, report-generation, large-language-models, nlp, information-retrieval, neurips-2025, deepsearch, webwalker, reasoning, research

lowcomparison#3

Add a 'Comparison with Alternatives' section to README

Why:

COPY-PASTE FIX

Add a new section, e.g., '## 💡 Comparison with Alternatives' or '## 🚀 Why WebThinker?', that briefly outlines how WebThinker stands out from general LLM frameworks or web scraping tools, focusing on its 'unified agent framework' for deep web research.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface RUC-NLPIR/WebThinker

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

SerpApi

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

SerpApi · recommended 2×
Beautiful Soup · recommended 2×
Playwright · recommended 2×
Selenium · recommended 2×
LangChain · recommended 2×

CATEGORY QUERY
How can I enhance large language models with deep web research capabilities for complex reasoning?
you: not recommended
AI recommended (in order):
1. SerpApi
2. Serper API
3. Beautiful Soup
4. Playwright
5. Selenium
6. LangChain
7. LlamaIndex
8. Wikidata Query Service
9. Diffbot
10. Common Crawl
AI recommended 10 alternatives but never named RUC-NLPIR/WebThinker. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Tools for building AI agents that perform comprehensive web research and generate detailed reports?
you: not recommended
AI recommended (in order):
1. LangChain
2. LlamaIndex
3. AutoGPT
4. BabyAGI
5. SerpApi
6. Google Custom Search API
7. Beautiful Soup
8. Playwright
9. Selenium
10. Pandas
11. ReportLab
12. FPDF
13. WeasyPrint
AI recommended 13 alternatives but never named RUC-NLPIR/WebThinker. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of RUC-NLPIR/WebThinker?
pass
AI named RUC-NLPIR/WebThinker explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts RUC-NLPIR/WebThinker in production, what risks or prerequisites should they evaluate first?
pass
AI named RUC-NLPIR/WebThinker explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo RUC-NLPIR/WebThinker solve, and who is the primary audience?
pass
AI named RUC-NLPIR/WebThinker explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/RUC-NLPIR/WebThinker.svg)](https://repogeo.com/en/r/RUC-NLPIR/WebThinker)

HTML

<a href="https://repogeo.com/en/r/RUC-NLPIR/WebThinker"><img src="https://repogeo.com/badge/RUC-NLPIR/WebThinker.svg" alt="RepoGEO" /></a>

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RUC-NLPIR/WebThinker — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite