REPOGEO REPORT · LITE

DestinyLinker/MingLi-Bench

Default branch main · commit b7433280 · scanned 6/6/2026, 9:33:07 PM

GitHub: 1,593 stars · 276 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)

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

AI VISIBILITY SCORE

28 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

2 / 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 DestinyLinker/MingLi-Bench, 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

hightopics#1
Add specific topics for LLM benchmarking and Chinese astrology
Why:
CURRENT
```
(none)
```
COPY-PASTE FIX
```
llm-benchmark, chinese-astrology, bazi, ziwei-doushu, large-language-models, nlp, evaluation
```
highreadme#2
Reposition README H1 to explicitly include 'LLM Benchmark'
Why:
CURRENT
```
# Chinese Fortune Telling Bench
```
COPY-PASTE FIX
```
# MingLi-Bench: LLM Benchmark for Chinese Fortune Telling
```

mediumreadme#3

Move unique data source mention to README's introductory section

Why:

CURRENT

The corpus is sourced from the annual **Global Fortune Teller Competition** (全球算命师大赛) for 2022–2025.

COPY-PASTE FIX

MingLi-Bench's corpus is uniquely sourced from the annual Global Fortune Teller Competition (全球算命师大赛) for 2022–2025.

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 DestinyLinker/MingLi-Bench

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Scale AI Data Platform

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Scale AI Data Platform · recommended 1×
Appen · recommended 1×
Prolific · recommended 1×
Qualtrics · recommended 1×
SurveyMonkey · recommended 1×

CATEGORY QUERY
How to assess large language model performance on traditional Chinese astrological predictions?
you: not recommended
AI recommended (in order):
1. Scale AI Data Platform
2. Appen
3. Prolific
4. Qualtrics
5. SurveyMonkey
6. LangChain
7. LlamaIndex
8. Sentence-BERT (SBERT)
9. Universal Sentence Encoder (USE)
10. SpaCy
11. Python
12. Regex (Regular Expressions)
13. GPT-4
14. Claude 3 Opus
15. OpenAI API
16. Anthropic API
AI recommended 16 alternatives but never named DestinyLinker/MingLi-Bench. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Where can I find a dataset to benchmark LLMs on East Asian divination practices?
you: not recommended
AI recommended (in order):
1. JSTOR
2. Academia.edu
3. ResearchGate
4. The I Ching (Book of Changes)
5. Reddit
6. Asian Art Museum
7. British Museum
8. Metropolitan Museum of Art
AI recommended 8 alternatives but never named DestinyLinker/MingLi-Bench. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
warn
Suggestion:
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 DestinyLinker/MingLi-Bench?
pass
AI did not name DestinyLinker/MingLi-Bench — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts DestinyLinker/MingLi-Bench in production, what risks or prerequisites should they evaluate first?
pass
AI named DestinyLinker/MingLi-Bench 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 DestinyLinker/MingLi-Bench solve, and who is the primary audience?
pass
AI named DestinyLinker/MingLi-Bench explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of DestinyLinker/MingLi-Bench. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/DestinyLinker/MingLi-Bench.svg)](https://repogeo.com/en/r/DestinyLinker/MingLi-Bench)

HTML

<a href="https://repogeo.com/en/r/DestinyLinker/MingLi-Bench"><img src="https://repogeo.com/badge/DestinyLinker/MingLi-Bench.svg" alt="RepoGEO" /></a>

Pro

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DestinyLinker/MingLi-Bench — 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