REPOGEO REPORT · LITE

openai/openai-openapi

Default branch master · commit 5162af98 · scanned 5/24/2026, 3:21:52 AM

GitHub: 2,399 stars · 498 forks

AI VISIBILITY SCORE

27 /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

1 / 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 openai/openai-openapi, 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 H1 and opening paragraph to clarify its role as the official OpenAPI spec for generative AI

Why:

CURRENT

# OpenAPI spec for the OpenAI API

The OpenAPI specification for the OpenAI API is available in this repository:

COPY-PASTE FIX

# Official OpenAPI Specification for the OpenAI API

This repository provides the official, canonical OpenAPI specification for the OpenAI API. It is the definitive source for generating robust API clients, integrating with OpenAI's generative AI services, and ensuring consistent programmatic interaction.

mediumtopics#2
Expand topics to include 'openapi', 'api-specification', and 'generative-ai'
Why:
CURRENT
```
openai, openai-api
```
COPY-PASTE FIX
```
openai, openai-api, openapi, api-specification, generative-ai, llm-api, client-generation
```

lowreadme#3

Add a 'Why use this?' section to the README to highlight the benefits of the official spec

Why:

COPY-PASTE FIX

## Why use the Official OpenAPI Spec?

This specification is maintained directly by OpenAI, ensuring it is always up-to-date and accurately reflects the latest API capabilities. It is ideal for:
- **Client Generation:** Automatically create type-safe API clients in any language.
- **Consistent Integration:** Build reliable integrations with OpenAI's models and services.
- **Tooling Compatibility:** Leverage a standard format for API documentation, testing, and development tools.

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 openai/openai-openapi

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

golang/go

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

golang/go · recommended 2×
dotnet/runtime · recommended 2×
OpenAI API · recommended 1×
Google Cloud Vertex AI API · recommended 1×
huggingface/transformers · recommended 1×

CATEGORY QUERY
Where can I find a standard API specification for integrating with generative AI services?
you: not recommended
AI recommended (in order):
1. OpenAI API
2. Google Cloud Vertex AI API
3. Hugging Face Transformers Library (huggingface/transformers)
4. Hugging Face Inference API
5. Anthropic Claude API
6. AWS Bedrock API
7. LangChain (langchain-ai/langchain)
AI recommended 7 alternatives but never named openai/openai-openapi. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What's the best way to develop custom clients for a large language model API?
you: not recommended
AI recommended (in order):
1. requests (psf/requests)
2. Pydantic (pydantic/pydantic)
3. axios (axios/axios)
4. Zod (colinhacks/zod)
5. net/http (golang/go)
6. encoding/json (golang/go)
7. OpenAPI Generator (OpenAPITools/openapi-generator)
8. reqwest (seanmonstar/reqwest)
9. serde (serde-rs/serde)
10. HttpClient (dotnet/runtime)
11. System.Text.Json (dotnet/runtime)
12. Newtonsoft.Json (JamesNK/Newtonsoft.Json)
AI recommended 12 alternatives but never named openai/openai-openapi. 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 openai/openai-openapi?
pass
AI did not name openai/openai-openapi — 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 openai/openai-openapi in production, what risks or prerequisites should they evaluate first?
pass
AI named openai/openai-openapi 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 openai/openai-openapi solve, and who is the primary audience?
pass
AI did not name openai/openai-openapi — 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?

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Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite