REPOGEO REPORT · LITE

noahshinn/reflexion

Default branch main · commit 218cf0ef · scanned 6/30/2026, 6:18:16 AM

GitHub: 3,191 stars · 310 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

35 /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

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 noahshinn/reflexion, 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 the README's first paragraph to emphasize problem-solving

Why:

CURRENT

# [NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning

This repo holds the code, demos, and log files for Reflexion: Language Agents with Verbal Reinforcement Learning by Noah Shinn, Federico Cassano, Edward Berman, Ashwin Gopinath, Karthik Narasimhan, Shunyu Yao.

COPY-PASTE FIX

# [NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning

This repository provides the official code, demos, and log files for Reflexion, a novel approach that empowers language agents to self-correct and improve their reasoning through verbal reinforcement learning. Developed by Noah Shinn et al. for NeurIPS 2023, Reflexion addresses the challenge of building robust LLM agents that learn from their mistakes.

hightopics#2

Add more specific topics to improve categorization

Why:

CURRENT

ai, artificial-intelligence, llm

COPY-PASTE FIX

ai, artificial-intelligence, llm, language-agents, self-correction, reinforcement-learning, reasoning, neurips, llm-agents

mediumhomepage#3
Add the NeurIPS paper URL as the repository homepage
Why:
COPY-PASTE FIX
```
https://arxiv.org/abs/2305.15390
```

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 noahshinn/reflexion

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

langchain-ai/langchain

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

langchain-ai/langchain · recommended 1×
run-llama/llama_index · recommended 1×
Significant-Gravitas/AutoGPT · recommended 1×
yoheinakajima/babyagi · recommended 1×
OpenAI Function Calling / Tool Use · recommended 1×

CATEGORY QUERY
How to build LLM agents that can self-correct and learn from mistakes?
you: not recommended
AI recommended (in order):
1. LangChain (langchain-ai/langchain)
2. LlamaIndex (run-llama/llama_index)
3. AutoGPT (Significant-Gravitas/AutoGPT)
4. BabyAGI (yoheinakajima/babyagi)
5. OpenAI Function Calling / Tool Use
6. Anthropic
7. TRL (Transformer Reinforcement Learning) (huggingface/trl)
8. requests (psf/requests)
9. json
10. openai (Python library) (openai/openai-python)
AI recommended 10 alternatives but never named noahshinn/reflexion. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a framework for language agents that improve reasoning with verbal feedback.
you: not recommended
AI recommended (in order):
1. LangChain
2. LlamaIndex
3. AutoGPT
4. Haystack
5. DSPy
AI recommended 5 alternatives but never named noahshinn/reflexion. 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 noahshinn/reflexion?
pass
AI named noahshinn/reflexion explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts noahshinn/reflexion in production, what risks or prerequisites should they evaluate first?
pass
AI named noahshinn/reflexion 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 noahshinn/reflexion solve, and who is the primary audience?
pass
AI named noahshinn/reflexion 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 noahshinn/reflexion. 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/noahshinn/reflexion.svg)](https://repogeo.com/en/r/noahshinn/reflexion)

HTML

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

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noahshinn/reflexion — 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