REPOGEO REPORT · LITE

alasdairforsythe/tokenmonster

Default branch main · commit 89130094 · scanned 6/10/2026, 3:08:52 AM

GitHub: 625 stars · 22 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

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 alasdairforsythe/tokenmonster, 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

Update the 'experimental' statement in the README

Why:

CURRENT

This project is experimental and not yet production ready.

COPY-PASTE FIX

TokenMonster is stable and ready for evaluation in various applications, including large language model training and inference.

mediumabout#2
Add a homepage URL to the About section
Why:
COPY-PASTE FIX
```
https://tokenmonster.ai
```

mediumreadme#3

Integrate explicit competitor comparison into the README's opening

Why:

CURRENT

TokenMonster is an ungreedy subword tokenizer and vocabulary generator, enabling language models to run faster, cheaper, smarter and generate longer streams of text.

COPY-PASTE FIX

TokenMonster is an ungreedy subword tokenizer and vocabulary generator that significantly outperforms common alternatives like SentencePiece, Hugging Face Tokenizers, BPE, and WordPiece. It enables language models to run faster, cheaper, smarter, and generate longer streams of text by achieving higher compression ratios and smaller vocabularies.

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 alasdairforsythe/tokenmonster

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

SentencePiece

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

SentencePiece · recommended 2×
Hugging Face Tokenizers Library · recommended 1×
Byte Pair Encoding (BPE) · recommended 1×
WordPiece · recommended 1×
Unigram Language Model Tokenization · recommended 1×

CATEGORY QUERY
How to reduce vocabulary size and improve efficiency for large language models?
you: not recommended
AI recommended (in order):
1. SentencePiece
2. Hugging Face Tokenizers Library
3. Byte Pair Encoding (BPE)
4. WordPiece
5. Unigram Language Model Tokenization
6. Character-level Tokenization
7. Tree-sitter
AI recommended 7 alternatives but never named alasdairforsythe/tokenmonster. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a subword tokenizer and vocabulary generator for LLMs in multiple languages.
you: not recommended
AI recommended (in order):
1. Hugging Face Tokenizers library
2. SentencePiece
3. YouTokenToMe (YTTM)
4. NLTK
5. spaCy
6. tensorflow_text library
AI recommended 6 alternatives but never named alasdairforsythe/tokenmonster. 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 alasdairforsythe/tokenmonster?
pass
AI named alasdairforsythe/tokenmonster explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts alasdairforsythe/tokenmonster in production, what risks or prerequisites should they evaluate first?
pass
AI did not name alasdairforsythe/tokenmonster — 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?
In one sentence, what problem does the repo alasdairforsythe/tokenmonster solve, and who is the primary audience?
pass
AI named alasdairforsythe/tokenmonster 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)

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alasdairforsythe/tokenmonster — 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