REPOGEO REPORT · LITE
google-deepmind/opro
Default branch main · commit a76bdce2 · scanned 6/9/2026, 5:42:43 PM
GitHub: 754 stars · 93 forks
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 google-deepmind/opro, 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.
- hightopics#1Add relevant topics to the repository
Why:
COPY-PASTE FIXllm-as-optimizer, prompt-optimization, large-language-models, generative-ai, machine-learning, deep-learning, ai-optimization, meta-learning, prompt-engineering
- highreadme#2Reposition the README's opening paragraph to highlight OPRO's unique value
Why:
CURRENT# Large Language Models as Optimizers This repository contains the code for the paper > Large Language Models as Optimizers > Chengrun Yang*, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen* [* Equal Contribution] > _arXiv: 2309.03409_
COPY-PASTE FIX# OPRO: Large Language Models as Optimizers This repository provides the official code for **OPRO (Optimizing Prompts for Reasoning)**, a novel framework that leverages Large Language Models *as optimizers* to iteratively generate, evaluate, and refine prompts for other LLMs. OPRO automates the discovery of effective prompts, offering a powerful alternative to manual prompt engineering for improving LLM performance on tasks like mathematical and combinatorial optimization.
- mediumabout#3Update the repository description to be more explicit about its function
Why:
CURRENTofficial code for "Large Language Models as Optimizers"
COPY-PASTE FIXOfficial code for OPRO: a framework that uses Large Language Models as optimizers to automatically generate and refine prompts for other LLMs, improving performance on various tasks.
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.
- PromptPerfect · recommended 2×
- LangChain · recommended 2×
- Weights & Biases Prompts · recommended 1×
- OpenAI Evals · recommended 1×
- Humanloop · recommended 1×
- CATEGORY QUERYHow can I automatically improve the performance of my large language model prompts?you: not recommendedAI recommended (in order):
- PromptPerfect
- Weights & Biases Prompts
- LangChain
- OpenAI Evals
- Humanloop
- Guardrails AI
- Microsoft Guidance
AI recommended 7 alternatives but never named google-deepmind/opro. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat tools help use language models to refine other language model instructions?you: not recommendedAI recommended (in order):
- Guidance
- LangChain
- LlamaIndex
- OpenAI API
- PromptPerfect
AI recommended 5 alternatives but never named google-deepmind/opro. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
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 google-deepmind/opro?passAI named google-deepmind/opro explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts google-deepmind/opro in production, what risks or prerequisites should they evaluate first?passAI named google-deepmind/opro 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 google-deepmind/opro solve, and who is the primary audience?passAI did not name google-deepmind/opro — 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?
Embed your GEO score
Drop this badge into the README of google-deepmind/opro. 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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google-deepmind/opro — 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