REPOGEO REPORT · LITE

castorini/anserini

Default branch master · commit 420530fd · scanned 6/18/2026, 9:57:43 PM

GitHub: 1,146 stars · 615 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 castorini/anserini, 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 opening to clarify research focus

Why:

CURRENT

Anserini is a toolkit for reproducible information retrieval research. By building on Lucene, we aim to bridge the gap between academic information retrieval research and the practice of building real-world search applications.

COPY-PASTE FIX

Anserini is a specialized toolkit for **reproducible information retrieval research**, built on Lucene. Unlike production search engines such as Elasticsearch or Solr, Anserini focuses on providing a robust, standardized platform for academic experimentation, benchmarking, and replicating IR studies.

hightopics#2

Add specific research-oriented topics

Why:

CURRENT

information-retrieval, lucene

COPY-PASTE FIX

information-retrieval, lucene, information-retrieval-research, ir-toolkit, reproducibility, academic-research

mediumreadme#3

Add a 'Comparison to Production Systems' section in README

Why:

COPY-PASTE FIX

### Anserini: Research Toolkit vs. Production Search Engine

Anserini is designed for academic research and experimentation, offering fine-grained control over IR models and reproducible results. It is not intended as a drop-in replacement for production-grade search engines like Elasticsearch, Apache Solr, or OpenSearch, which are optimized for scalability, operational robustness, and diverse application use cases. While Anserini leverages Lucene, its primary goal is to advance IR science, not to power large-scale commercial applications.

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 castorini/anserini

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Elasticsearch

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Elasticsearch · recommended 2×
Apache Solr · recommended 2×
OpenSearch · recommended 2×
Apache Lucene · recommended 2×
Weaviate · recommended 1×

CATEGORY QUERY
How to build a robust search application with reproducible information retrieval capabilities?
you: not recommended
AI recommended (in order):
1. Elasticsearch
2. Apache Solr
3. OpenSearch
4. Weaviate
5. Faiss
6. Apache Lucene
7. PostgreSQL
8. pg_trgm
9. pg_vector
AI recommended 9 alternatives but never named castorini/anserini. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best open-source toolkits for information retrieval research using Lucene?
you: not recommended
AI recommended (in order):
1. Apache Lucene
2. Apache Solr
3. Elasticsearch
4. Lucene.Net
5. PyLucene
6. OpenSearch
AI recommended 6 alternatives but never named castorini/anserini. 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 castorini/anserini?
pass
AI named castorini/anserini explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts castorini/anserini in production, what risks or prerequisites should they evaluate first?
pass
AI named castorini/anserini 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 castorini/anserini solve, and who is the primary audience?
pass
AI named castorini/anserini 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 castorini/anserini. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/castorini/anserini.svg)](https://repogeo.com/en/r/castorini/anserini)

HTML

<a href="https://repogeo.com/en/r/castorini/anserini"><img src="https://repogeo.com/badge/castorini/anserini.svg" alt="RepoGEO" /></a>

Pro

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castorini/anserini — 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