Agent skill

OmniRoute Inference Endpoints

by diegosouzapw in diegosouzapw/OmniRoute

Documents OmniRoute's OpenAI-compatible endpoints for chat completions, embeddings, images, speech, transcription, moderation, rerank and the Responses API.

MITAuto-check passedAI & LLM Engineering

Install OmniRoute Inference Endpoints

skills CLI

$ npx skills add diegosouzapw/OmniRoute --skill omni-inference -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install diegosouzapw/OmniRoute omni-inference --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/diegosouzapw/OmniRoute.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/omni-inference .claude/skills/omni-inference && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "omni-inference" agent skill from https://github.com/diegosouzapw/OmniRoute/tree/release%2Fv3.8.52/skills/omni-inference into .claude/skills/omni-inference/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "omni-inference", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/diegosouzapw/OmniRoute/tree/release%2Fv3.8.52/skills/omni-inference

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add diegosouzapw/OmniRoute --skill omni-inference -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install diegosouzapw/OmniRoute omni-inference --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/diegosouzapw/OmniRoute.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/omni-inference .agents/skills/omni-inference && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "omni-inference" agent skill from https://github.com/diegosouzapw/OmniRoute/tree/release%2Fv3.8.52/skills/omni-inference into .agents/skills/omni-inference/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "omni-inference", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add diegosouzapw/OmniRoute --skill omni-inference -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install diegosouzapw/OmniRoute omni-inference --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/diegosouzapw/OmniRoute.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/omni-inference .cursor/skills/omni-inference && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "omni-inference" agent skill from https://github.com/diegosouzapw/OmniRoute/tree/release%2Fv3.8.52/skills/omni-inference into .cursor/skills/omni-inference/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "omni-inference", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/diegosouzapw/OmniRoute.git --path skills/omni-inference

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add diegosouzapw/OmniRoute --skill omni-inference -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install diegosouzapw/OmniRoute omni-inference --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/diegosouzapw/OmniRoute.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/omni-inference .gemini/skills/omni-inference && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "omni-inference" agent skill from https://github.com/diegosouzapw/OmniRoute/tree/release%2Fv3.8.52/skills/omni-inference into .gemini/skills/omni-inference/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "omni-inference", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install diegosouzapw/OmniRoute omni-inference

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add diegosouzapw/OmniRoute --skill omni-inference -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/diegosouzapw/OmniRoute.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/omni-inference .github/skills/omni-inference && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "omni-inference" agent skill from https://github.com/diegosouzapw/OmniRoute/tree/release%2Fv3.8.52/skills/omni-inference into .github/skills/omni-inference/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "omni-inference", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add diegosouzapw/OmniRoute --skill omni-inference -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install diegosouzapw/OmniRoute omni-inference --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/diegosouzapw/OmniRoute.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/omni-inference .opencode/skills/omni-inference && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "omni-inference" agent skill from https://github.com/diegosouzapw/OmniRoute/tree/release%2Fv3.8.52/skills/omni-inference into .opencode/skills/omni-inference/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "omni-inference", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: omni-inference
GitHub stars: 74k
Token cost: ~5.5k tokens
SKILL.md length: 866 words
Files: 2 (incl. references)
Skills in repo: 50
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Documents OmniRoute's OpenAI-compatible endpoints for chat completions, embeddings, images, speech, transcription, moderation, rerank and the Responses API.

Pointing an agent at OmniRoute's chat completions endpoint
SKILL.md covers Overview, Authentication, Endpoints and Payloads, plus 5 more sections
Calls curl and jq; reaches anthropic.com; needs OMNIROUTE_KEY and REQUIRE_API_KEY
Generating embeddings or images through the gateway

What it does

The main integration surface that OmniRoute offers to AI agents. Its routes follow the OpenAI shape: chat completions, embeddings, image generation, audio speech and transcription, moderations, rerank and the Responses API. Provider-specific variants of the chat, embeddings and image routes sit under a providers path.

The endpoint list also includes web search, session leases, a WebSocket route, a messages route with token counting, multimodal embeddings and a models listing per provider. Full details are in references/endpoints.md. Authentication is a Bearer token or session cookie, and REQUIRE_API_KEY=false is the local development switch.

When your agent uses it

Pointing an agent at OmniRoute's chat completions endpoint
Generating embeddings or images through the gateway
Transcribing audio or synthesizing speech through one API
Counting tokens before sending a message

Example prompts

“Call OmniRoute's embeddings endpoint on these three paragraphs.”
“Send this prompt to the chat completions route of my gateway.”
“Transcribe meeting.mp3 through the OmniRoute audio transcription endpoint.”

Requirements

A running OmniRoute instance
A Bearer token or session cookie

What it can do on your machine

Read from SKILL.md and the folder at commit f8a8131. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- curl
- jq
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- anthropic.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- OMNIROUTE_KEY
- REQUIRE_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

OmniRoute Inference Endpoints loads about 5.5k tokens when it runs, and up to ~16k if it reads all its reference files. Until then it costs about 52 tokens; SKILL.md has 866 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~52
When it runs · the whole SKILL.md, loaded when a task matches: ~5.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~16k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from diegosouzapw/OmniRoute at commit f8a8131, republished under its MIT licence (© diegosouzapw). 866 words, ~5,465 tokens.

Download SKILL.mdSave it as .claude/skills/omni-inference/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: omni-inference
description: The core OpenAI-compatible inference endpoints: chat completions, embeddings, images, audio (TTS/STT), moderations, rerank, and the Responses API. The primary integration surface for AI agents.

<!-- generated by src/lib/agentSkills/generator.ts; manual edits will be overwritten -->

Overview

The core OpenAI-compatible inference endpoints: chat completions, embeddings, images, audio (TTS/STT), moderations, rerank, and the Responses API. The primary integration surface for AI agents.

Authentication

All requests require a valid Bearer token or session cookie. Obtain a token via POST /api/auth/login or configure REQUIRE_API_KEY=false for local development.

Endpoints

Payloads

See the full OpenAPI specification at GET /api/openapi/spec or docs/openapi.yaml for detailed request/response schemas.

<!-- skill:custom-start -->

<!-- Aggregated from: omniroute-chat, omniroute-image, omniroute-tts, omniroute-stt, omniroute-embeddings, omniroute-web-search, omniroute-web-fetch -->

Chat completions

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoints

POST $OMNIROUTE_URL/v1/chat/completions — OpenAI format
POST $OMNIROUTE_URL/v1/messages — Anthropic Messages format
POST $OMNIROUTE_URL/v1/responses — OpenAI Responses API

Discover

bash

curl $OMNIROUTE_URL/v1/models | jq '.data[].id'

Combos (e.g. auto, cost-optimized, subscription) auto-fallback through multiple providers.

OpenAI format example

bash

curl -X POST $OMNIROUTE_URL/v1/chat/completions \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "messages": [{"role": "user", "content": "Refactor this function"}],
    "stream": true
  }'

Anthropic format example

bash

curl -X POST $OMNIROUTE_URL/v1/messages \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "max_tokens": 4096,
    "messages": [{"role": "user", "content": "Hi"}]
  }'

Tool use

Supports OpenAI tools array and Anthropic tools block. Tool results auto-compressed via RTK (47 filters: git-diff, grep, test-jest, terraform-plan, docker-logs, etc.) — 20-40% token savings. Disable per-request with X-Omniroute-Rtk: off header.

Reasoning / thinking

Anthropic extended thinking and OpenAI Responses reasoning blocks are forwarded verbatim. Cached automatically via reasoning cache.

Errors

401 → invalid API key
400 invalid_model → model not in registry; check /v1/models
503 circuit_open → provider circuit breaker tripped; retry later or use combo
429 rate_limited → honor Retry-After; consider using a combo for auto-fallback

Image generation

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoints

POST $OMNIROUTE_URL/v1/images/generations — Text-to-image
POST $OMNIROUTE_URL/v1/images/edits — Image edit (mask)
POST $OMNIROUTE_URL/v1/images/variations — Variations

Discover

bash

curl $OMNIROUTE_URL/v1/models/image | jq '.data[]'

Returns { id, owned_by, sizes:[...], capabilities:[...] } per model.

Generate example

bash

curl -X POST $OMNIROUTE_URL/v1/images/generations \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "dall-e-3",
    "prompt": "a red bicycle on a wet street, photoreal",
    "n": 1,
    "size": "1024x1024",
    "response_format": "b64_json"
  }'

Response: { created, data: [{ url? or b64_json, revised_prompt }] }

Errors

400 invalid_size → not supported by this model; check /v1/models/image
400 content_policy_violation → blocked by provider safety
503 → provider unavailable; try another model in /v1/models/image

Show full SKILL.md (359 more words)Show less

Text-to-speech

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoint

POST $OMNIROUTE_URL/v1/audio/speech — returns binary audio (mp3/opus/wav/flac)

Discover

bash

curl $OMNIROUTE_URL/v1/models/tts | jq '.data[]'

Each entry includes voices:[...] for the available voice names per provider.

Example

bash

curl -X POST $OMNIROUTE_URL/v1/audio/speech \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1",
    "input": "Hello from OmniRoute.",
    "voice": "alloy",
    "response_format": "mp3"
  }' --output speech.mp3

Voices

Voice names vary by provider. Check /v1/models/tts — each entry has voices:[...]. Common OpenAI voices: alloy, echo, fable, onyx, nova, shimmer.

Errors

400 invalid_voice → voice not supported by this model
400 input_too_long → input exceeds model character limit
503 → provider unavailable; try another model in /v1/models/tts

Speech-to-text

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoints

POST $OMNIROUTE_URL/v1/audio/transcriptions — multipart upload, returns text
POST $OMNIROUTE_URL/v1/audio/translations — transcribe + translate to English

Discover

bash

curl $OMNIROUTE_URL/v1/models/stt | jq '.data[]'

Example

bash

curl -X POST $OMNIROUTE_URL/v1/audio/transcriptions \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -F "file=@audio.mp3" \
  -F "model=whisper-1" \
  -F "response_format=verbose_json"

Response: { text, language, duration, segments?:[{ start, end, text }] }

Supported formats

Audio: mp3, mp4, mpeg, mpga, m4a, wav, webm. Response formats: json, text, srt, verbose_json, vtt.

Errors

400 invalid_file_format → unsupported audio format
400 file_too_large → exceeds provider limit (usually 25MB)
503 → provider unavailable; try another model in /v1/models/stt

Embeddings

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoint

POST $OMNIROUTE_URL/v1/embeddings

Discover

bash

curl $OMNIROUTE_URL/v1/models/embedding | jq '.data[]'

Each entry: { id, owned_by, dimensions, max_input_tokens }.

Example

bash

curl -X POST $OMNIROUTE_URL/v1/embeddings \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-large",
    "input": ["first text", "second text"],
    "encoding_format": "float"
  }'

Response: { data:[{ embedding:[...], index }], usage:{ prompt_tokens, total_tokens } }

Batch input

input accepts a string or array of strings (up to provider batch limit, typically 2048 items).

Errors

400 input_too_long → input exceeds max_input_tokens for this model
400 invalid_encoding_format → use float or base64
503 → provider unavailable; try another model in /v1/models/embedding

Web search

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoint

POST $OMNIROUTE_URL/v1/web/search — unified search format

Discover

bash

curl $OMNIROUTE_URL/v1/models/web | jq '.data[] | select(.kind == "webSearch")'

Example

bash

curl -X POST $OMNIROUTE_URL/v1/web/search \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tavily/search",
    "query": "OmniRoute github latest release",
    "max_results": 5,
    "include_answer": true
  }'

Response: { answer?, results:[{ url, title, content, score }] }

Parameters

Field	Type	Description
`model`	string	Provider model from `/v1/models/web`
`query`	string	Search query
`max_results`	number	Max results (default: 5)
`include_answer`	boolean	Include AI-synthesized answer
`search_depth`	string	`basic` or `advanced` (Tavily)

Errors

400 query_too_long → shorten the search query
503 → provider unavailable; try another model in /v1/models/web

Web fetch

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoint

POST $OMNIROUTE_URL/v1/web/fetch

Discover

bash

curl $OMNIROUTE_URL/v1/models/web | jq '.data[] | select(.kind == "webFetch")'

Example

bash

curl -X POST $OMNIROUTE_URL/v1/web/fetch \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "jina/reader",
    "url": "https://anthropic.com",
    "format": "markdown"
  }'

Response: { url, title, markdown, links?:[...], images?:[...] }

Parameters

Field	Type	Description
`model`	string	Provider from `/v1/models/web` (e.g. `jina/reader`, `firecrawl/scrape`)
`url`	string	URL to fetch
`format`	string	`markdown` (default), `html`, `text`

Errors

400 invalid_url → URL must be http/https
403 blocked → provider blocked by target site; try a different model
503 → provider unavailable; try another model in /v1/models/web

<!-- skill:custom-end -->

Files

SKILL.md and 1 other file (references) in skills/omni-inference of diegosouzapw/OmniRoute.

SKILL.md
references/endpoints.md

Open the folder on GitHubat commit f8a8131

Compare with similar skills

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OmniRoute Inference Endpoints compared with similar skills
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Questions about OmniRoute Inference Endpoints

What does OmniRoute Inference Endpoints do?

Documents OmniRoute's OpenAI-compatible endpoints for chat completions, embeddings, images, speech, transcription, moderation, rerank and the Responses API. The main integration surface that OmniRoute offers to AI agents. Its routes follow the OpenAI shape: chat completions, embeddings, image generation, audio speech and transcription, moderations, rerank and the Responses API.

When should I use OmniRoute Inference Endpoints?

OmniRoute Inference Endpoints fits situations like: pointing an agent at OmniRoute's chat completions endpoint; generating embeddings or images through the gateway; transcribing audio or synthesizing speech through one API; counting tokens before sending a message.

How do I install OmniRoute Inference Endpoints in Claude Code?

Run `npx skills add diegosouzapw/OmniRoute --skill omni-inference -a claude-code`. Or copy the skill folder (skills/omni-inference in diegosouzapw/OmniRoute) into .claude/skills/omni-inference in your project. Claude Code loads it when a task matches its description.

How do I install OmniRoute Inference Endpoints in Codex?

Run `npx skills add diegosouzapw/OmniRoute --skill omni-inference -a codex`. Or copy the skill folder (skills/omni-inference in diegosouzapw/OmniRoute) into .agents/skills/omni-inference in your project. Codex loads it when a task matches its description.

Can I use OmniRoute Inference Endpoints in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add diegosouzapw/OmniRoute --skill omni-inference -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/omni-inference, .gemini/skills/omni-inference, .github/skills/omni-inference and .opencode/skills/omni-inference in your project.

What does OmniRoute Inference Endpoints need to run?

Going by SKILL.md and its folder, OmniRoute Inference Endpoints needs the command-line tools its instructions call (curl and jq) and credentials named OMNIROUTE_KEY and REQUIRE_API_KEY. Our summary lists: A running OmniRoute instance; A Bearer token or session cookie.

Does OmniRoute Inference Endpoints access the network?

SKILL.md names 1 domain. In commands or code: anthropic.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is OmniRoute Inference Endpoints safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does OmniRoute Inference Endpoints use?

OmniRoute Inference Endpoints is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does OmniRoute Inference Endpoints use?

About 5.5k tokens (SKILL.md is roughly 22k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.

What are the alternatives to OmniRoute Inference Endpoints?

Skills that share tags, products or a category with OmniRoute Inference Endpoints: Caching Architecture (majiayu000/litellm-rs, 117 stars), Llmobs Integration (DataDog/dd-trace-js, 836 stars), Keirouter (mydisha/keirouter, 147 stars) and Cognee Integrations Setup (topoteretes/cognee, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains OmniRoute Inference Endpoints?

diegosouzapw (a GitHub user) maintains it in diegosouzapw/OmniRoute, which has 74,003 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on October 8, 2026.

Source: diegosouzapw/OmniRoute on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install OmniRoute Inference Endpoints

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Overview

Authentication

Endpoints

Payloads

Chat completions

Endpoints

Discover

OpenAI format example

Anthropic format example

Tool use

Reasoning / thinking

Errors

Image generation

Endpoints

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Generate example

Errors

Text-to-speech

Endpoint

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Example

Voices

Errors

Speech-to-text

Endpoints

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Example

Supported formats

Errors

Embeddings

Endpoint

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Example

Batch input

Errors

Web search

Endpoint

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Example

Parameters

Errors

Web fetch

Endpoint

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Example

Parameters

Errors

Files

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