Azure AI Openai Dotnet
microsoft/skills
Azure OpenAI SDK for .NET. An agent skill from microsoft/skills.
Send inference requests through the FastLLM OpenAI-compatible gateway — chat completions, completions, embeddings, rerank, score, responses, moderations, audio speech and transcription, image…
Install Fastllm Gateway
$ npx skills add azrtydxb/Fastllm-proxy --skill fastllm-gateway -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-gateway --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/azrtydxb/Fastllm-proxy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/fastllm-gateway .claude/skills/fastllm-gateway && rm -rf skills-srcUse ~/.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/
Install the "fastllm-gateway" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-gateway into .claude/skills/fastllm-gateway/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-gateway", 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 install https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-gatewayType 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.
$ npx skills add azrtydxb/Fastllm-proxy --skill fastllm-gateway -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-gateway --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/azrtydxb/Fastllm-proxy.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/fastllm-gateway .agents/skills/fastllm-gateway && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "fastllm-gateway" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-gateway into .agents/skills/fastllm-gateway/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-gateway", 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.
$ npx skills add azrtydxb/Fastllm-proxy --skill fastllm-gateway -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-gateway --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/azrtydxb/Fastllm-proxy.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/fastllm-gateway .cursor/skills/fastllm-gateway && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "fastllm-gateway" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-gateway into .cursor/skills/fastllm-gateway/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-gateway", 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 https://github.com/azrtydxb/Fastllm-proxy.git --path .claude/skills/fastllm-gateway--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add azrtydxb/Fastllm-proxy --skill fastllm-gateway -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-gateway --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/azrtydxb/Fastllm-proxy.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/fastllm-gateway .gemini/skills/fastllm-gateway && rm -rf skills-srcUse ~/.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/
Install the "fastllm-gateway" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-gateway into .gemini/skills/fastllm-gateway/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-gateway", 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.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-gatewayInstalls 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).
$ npx skills add azrtydxb/Fastllm-proxy --skill fastllm-gateway -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/azrtydxb/Fastllm-proxy.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/fastllm-gateway .github/skills/fastllm-gateway && rm -rf skills-srcUse ~/.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/
Install the "fastllm-gateway" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-gateway into .github/skills/fastllm-gateway/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-gateway", 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.
$ npx skills add azrtydxb/Fastllm-proxy --skill fastllm-gateway -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-gateway --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/azrtydxb/Fastllm-proxy.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/fastllm-gateway .opencode/skills/fastllm-gateway && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "fastllm-gateway" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-gateway into .opencode/skills/fastllm-gateway/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-gateway", 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
fastllm-gateway- GitHub stars
- 108
- Token cost
- ~926 tokens
- SKILL.md length
- 383 words
- Files
- 1
- Skills in repo
- 14
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Send inference requests through the FastLLM OpenAI-compatible gateway — chat completions, completions, embeddings, rerank, score, responses, moderations, audio speech and transcription, image…
- Calling a model through the proxy
- SKILL.md covers Auth and Traps
- Calls curl
- Testing that a model
What it does
Fastllm Gateway is an agent skill from azrtydxb/Fastllm-proxy. Send inference requests through the FastLLM OpenAI-compatible gateway — chat completions, completions, embeddings, rerank, score, responses, moderations, audio speech and transcription, image generation and edits, and listing available models. Use when calling a model through the proxy, testing that a model or frontend model actually serves, or debugging a 401, 404 or 503 from a client.
Its SKILL.md is about 930 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering LLM API integration, Embeddings and Transcription. It works with OpenAI. The repository describes itself as: The lowest-overhead LLM router. Production-ready, highly available, one OpenAI-compatible endpoint in front of 80 providers and your own vLLM/SGLang — 0.76 µs per request, no I/O… The licence is Apache-2.0.
When your agent uses it
- Calling a model through the proxy
- Testing that a model
- Frontend model actually serves
- Debugging a 401
Example prompts
- “/fastllm-gateway”
What it can do on your machine
Read from SKILL.md and the folder at commit 59a47cf. 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
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Fastllm Gateway loads about 926 tokens when it runs. Until then it costs about 101 tokens; SKILL.md has 383 words of instructions outside code blocks.
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 azrtydxb/Fastllm-proxy at commit 59a47cf, republished under its Apache-2.0 licence (© azrtydxb). 383 words, ~926 tokens.
Download SKILL.mdSave it as
.claude/skills/fastllm-gateway/SKILL.md (or your agent's skills folder).- name
- fastllm-gateway
- description
- Send inference requests through the FastLLM OpenAI-compatible gateway — chat completions, completions, embeddings, rerank, score, responses, moderations, audio speech and transcription, image generation and edits, and listing available models. Use when calling a model through the proxy, testing that a model or frontend model actually serves, or debugging a 401, 404 or 503 from a client.
FastLLM gateway
Auth
The gateway takes a principal API key as a bearer token — a different
credential from the admin session. Keys are stored SHA-256 hashed and cannot be
read back from the database; if you do not have one, you cannot call /v1/*.
curl http://192.168.10.125/v1/chat/completions -H "Authorization: Bearer <key>" \
-H 'content-type: application/json' -d '{"model":"<name>","messages":[...]}'<!-- BEGIN GENERATED: endpoints -->| Method | Path | Summary | Body fields |
|---|---|---|---|
POST | /v1/audio/speech | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/audio/transcriptions | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/audio/translations | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/chat/completions | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/completions | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/embeddings | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/images/edits | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/images/generations | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/messages | Anthropic Messages API. Translated to a chat completion and served by the ordinary request path, so routing, budgets, rate limits and RBAC apply unchanged | — |
POST | /v1/messages/count_tokens | Best-effort input token count for a Messages request. An estimate from the text, answered locally | — |
GET | /v1/models | Models this key may invoke. Filtered by the caller's grants. Anthropic-shaped when the request carries anthropic-version | — |
POST | /v1/moderations | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/rerank | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/responses | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
POST | /v1/score | Proxied to the backend serving model. Forwarded byte-for-byte for an openai backend | — |
* optional field
<!-- END GENERATED: endpoints -->Show full SKILL.md (103 more words)Show less
Traps
401 means the gateway is healthy. It reached the proxy and was rejected for
credentials. A connection refused or 000 is the failure worth chasing.
404 model_not_found on a frontend model means no viable target, not an
unknown name — check the chain resolves to something routable.
An unknown model name is a 404 regardless of permissions, deliberately, so "403 vs 404" cannot be used to probe which models exist.
Reasoning field names differ by backend engine. vLLM emits reasoning;
SGLang emits reasoning_content. A client hardcoded to one shows blank reasoning
against the other — check both before concluding a model is not thinking.
© azrtydxb, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .claude/skills/fastllm-gateway of azrtydxb/Fastllm-proxy.
Open the folder on GitHubat commit 59a47cf
Compare with similar skills
Fastllm Gateway next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Fastllm Gateway this skillazrtydxb/Fastllm-proxy | 108 | — | ~926 | Automated safety check: Pass | Apache-2.0 | |
| Azure AI Openai Dotnetmicrosoft/skills | 3.1k | 5 repos | ~3.4k | Automated safety check: Pass | MIT | |
| Xsaimoeru-ai/airi | 50k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Local AI App Integrationamd/skills | 408 | — | ~6k | Automated safety check: Pass | MIT | |
| AI Image GenZJU-REAL/Easel | 3.4k | — | ~787 | Automated safety check: Notes | Apache-2.0 | |
| Unified LLM APIPrism-Shadow/penguin-harness | 2.5k | — | ~6.7k | Automated safety check: Pass | Apache-2.0 |
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More from azrtydxb/Fastllm-proxy
All 14 skills in this repoFastllm Agents
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Manage and invoke A2A agents behind FastLLM — register, patch, delete and list agents on the control plane, list them through the gateway, fetch an agent card, and invoke an agent by name.
Fastllm Backends
azrtydxb/Fastllm-proxy
Run and troubleshoot the inference backends on the DGX Spark pair that FastLLM proxies to — starting or stopping models with vLLM, SGLang or sparkrun, choosing memory and speculative-decoding…
Fastllm Classifier
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Manage FastLLM prompt classes for semantic routing — create classes and their example prompts, list or delete them, and evaluate how a given prompt would be classified.
Fastllm Deployment
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Inspect and control the running FastLLM deployment — read effective configuration and deployment settings, force a snapshot rebuild, fetch the snapshot the proxies consume, and check liveness and…
Fastllm MCP
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Manage and use MCP servers behind FastLLM — register, patch, delete and list MCP servers on the control plane, and list or call their tools through the gateway.
Fastllm Models
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Register and maintain the models FastLLM can serve — create, patch or delete a model, attach backends to it, remove a backend, and set the deployment-wide fallback model.
Related
Works with
Categories
Questions about Fastllm Gateway
What does Fastllm Gateway do?
Send inference requests through the FastLLM OpenAI-compatible gateway — chat completions, completions, embeddings, rerank, score, responses, moderations, audio speech and transcription, image…. Fastllm Gateway is an agent skill from azrtydxb/Fastllm-proxy. Send inference requests through the FastLLM OpenAI-compatible gateway — chat completions, completions, embeddings, rerank, score, responses, moderations, audio speech and transcription, image generation and edits, and listing available models.
When should I use Fastllm Gateway?
Fastllm Gateway fits situations like: calling a model through the proxy; testing that a model; frontend model actually serves; debugging a 401.
How do I install Fastllm Gateway in Claude Code?
Run `npx skills add azrtydxb/Fastllm-proxy --skill fastllm-gateway -a claude-code`. Or copy the skill folder (.claude/skills/fastllm-gateway in azrtydxb/Fastllm-proxy) into .claude/skills/fastllm-gateway in your project. Claude Code loads it when a task matches its description.
How do I install Fastllm Gateway in Codex?
Run `npx skills add azrtydxb/Fastllm-proxy --skill fastllm-gateway -a codex`. Or copy the skill folder (.claude/skills/fastllm-gateway in azrtydxb/Fastllm-proxy) into .agents/skills/fastllm-gateway in your project. Codex loads it when a task matches its description.
Can I use Fastllm Gateway 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 azrtydxb/Fastllm-proxy --skill fastllm-gateway -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fastllm-gateway, .gemini/skills/fastllm-gateway, .github/skills/fastllm-gateway and .opencode/skills/fastllm-gateway in your project.
What does Fastllm Gateway need to run?
Going by SKILL.md and its folder, Fastllm Gateway needs the command-line tools its instructions call (curl).
Does Fastllm Gateway access the network?
SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Fastllm Gateway 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 Fastllm Gateway use?
Fastllm Gateway is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Fastllm Gateway use?
About 926 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Fastllm Gateway?
Skills that share tags, products or a category with Fastllm Gateway: Azure AI Openai Dotnet (microsoft/skills, 3.1k stars), Xsai (moeru-ai/airi, 50k stars), Local AI App Integration (amd/skills, 408 stars) and AI Image Gen (ZJU-REAL/Easel, 3.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Fastllm Gateway?
azrtydxb (a GitHub organization) maintains it in azrtydxb/Fastllm-proxy, which has 108 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 10, 2026.
Source: azrtydxb/Fastllm-proxy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.