REPOGEO REPORT · LITE

ggozad/oterm

Default branch main · commit 5f4e4dd1 · scanned 5/22/2026, 11:17:04 AM

GitHub: 2,383 stars · 134 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 ggozad/oterm, 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 opening sentence to emphasize LLM focus

Why:

CURRENT

The terminal client for Ollama, OpenAI, Anthropic, and any pydantic-ai-supported provider.

COPY-PASTE FIX

**Oterm is the terminal client for LLMs**, supporting Ollama, OpenAI, Anthropic, and any pydantic-ai-supported provider.

mediumtopics#2

Expand repository topics for better category matching

Why:

CURRENT

llm, llms, machine-learning, ollama, python, terminal

COPY-PASTE FIX

llm, llms, machine-learning, ollama, python, terminal, cli, chat, ai-chat, multi-provider, terminal-ui

mediumreadme#3

Add a 'Key Features' section to the README

Why:

COPY-PASTE FIX

## Key Features

*   **Multi-provider support:** Seamlessly interact with Ollama, OpenAI, Anthropic, Google, Groq, Mistral, and more, all from your terminal.
*   **Rich chat UI:** Enjoy a borderless, accent-driven layout, auto-growing prompt, inline image attachment tokens, and live token-usage display.
*   **Fast streaming:** Markdown updates incrementally for smooth, responsive long responses.
*   **Unified API:** Compatible with `pydantic-ai`'s standard schema for consistent configuration across providers.

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 ggozad/oterm

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

OpenAI Python Library

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

OpenAI Python Library · recommended 2×
LM Studio · recommended 1×
Ollama · recommended 1×
LiteLLM · recommended 1×
Hugging Face `transformers` Library · recommended 1×

CATEGORY QUERY
How to chat with large language models directly from a terminal interface?
you: not recommended
AI recommended (in order):
1. LM Studio
2. Ollama
3. LiteLLM
4. OpenAI Python Library
5. Hugging Face `transformers` Library
6. `curl`
AI recommended 6 alternatives but never named ggozad/oterm. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a command-line tool to manage multiple AI model APIs.
you: not recommended
AI recommended (in order):
1. LiteLLM (BerriAI/litellm)
2. OpenAI Python Library
3. openai (openai/openai-python)
4. anthropic (anthropic/anthropic-sdk-python)
5. google-cloud-aiplatform (googleapis/python-aiplatform)
6. Click (pallets/click)
7. Typer (tiangolo/typer)
8. LangChain CLI (langchain-ai/langchain)
9. Hugging Face Transformers CLI (huggingface/transformers)
10. LMQL (eth-sri/lmql)
11. Ollama (ollama/ollama)
AI recommended 11 alternatives but never named ggozad/oterm. 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 ggozad/oterm?
pass
AI did not name ggozad/oterm — 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 ggozad/oterm in production, what risks or prerequisites should they evaluate first?
pass
AI named ggozad/oterm 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 ggozad/oterm solve, and who is the primary audience?
pass
AI named ggozad/oterm 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 ggozad/oterm. 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/ggozad/oterm.svg)](https://repogeo.com/en/r/ggozad/oterm)

HTML

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

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ggozad/oterm — 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