Tianji Worker Operations
msgbyte/tianji
Operates Tianji Workers: create, test, deploy, invoke, schedule, pause and roll back them, plus manage their environment variables and shared modules.
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…
Install Fastllm Deployment
$ npx skills add azrtydxb/Fastllm-proxy --skill fastllm-deployment -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-deployment --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-deployment .claude/skills/fastllm-deployment && 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-deployment" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-deployment into .claude/skills/fastllm-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-deployment", 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-deploymentType 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-deployment -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-deployment --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-deployment .agents/skills/fastllm-deployment && 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-deployment" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-deployment into .agents/skills/fastllm-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-deployment", 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-deployment -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-deployment --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-deployment .cursor/skills/fastllm-deployment && 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-deployment" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-deployment into .cursor/skills/fastllm-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-deployment", 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-deployment--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-deployment -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install azrtydxb/Fastllm-proxy fastllm-deployment --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-deployment .gemini/skills/fastllm-deployment && 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-deployment" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-deployment into .gemini/skills/fastllm-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-deployment", 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-deploymentInstalls 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-deployment -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-deployment .github/skills/fastllm-deployment && 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-deployment" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-deployment into .github/skills/fastllm-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-deployment", 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-deployment -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-deployment --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-deployment .opencode/skills/fastllm-deployment && 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-deployment" agent skill from https://github.com/azrtydxb/Fastllm-proxy/tree/main/.claude/skills/fastllm-deployment into .opencode/skills/fastllm-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastllm-deployment", 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-deployment- GitHub stars
- 108
- Token cost
- ~727 tokens
- SKILL.md length
- 297 words
- Files
- 1
- Skills in repo
- 14
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
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…
- A configuration change has not taken effect
- SKILL.md covers Auth and Traps
- Calls curl
- A proxy is serving stale policy
What it does
Fastllm Deployment is an agent skill from azrtydxb/Fastllm-proxy. 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 readiness. Use when a configuration change has not taken effect, when a proxy is serving stale policy, or to confirm what a running instance actually believes.
Its SKILL.md is about 730 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 DevOps & Cloud, covering Deployment. It works with OpenAPI. 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
- A configuration change has not taken effect
- A proxy is serving stale policy
- Confirm what a running instance actually believes
Example prompts
- “/fastllm-deployment”
What it can do on your machine
Read from SKILL.md and the folder at commit 5d53db8. 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 Deployment loads about 727 tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 297 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 5d53db8, republished under its Apache-2.0 licence (© azrtydxb). 297 words, ~727 tokens.
Download SKILL.mdSave it as
.claude/skills/fastllm-deployment/SKILL.md (or your agent's skills folder).- name
- fastllm-deployment
- description
- 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 readiness. Use when a configuration change has not taken effect, when a proxy is serving stale policy, or to confirm what a running instance actually believes.
FastLLM deployment
Auth
Admin endpoints need a session cookie, not a bearer token — the gateway master key is not an admin credential.
curl -sk -c /tmp/ck -X POST https://192.168.10.129:4001/login \
-H 'content-type: application/json' -d '{"name":"<user>","password":"<pw>"}'
curl -sk -b /tmp/ck https://192.168.10.129:4001/admin/...<!-- BEGIN GENERATED: endpoints -->| Method | Path | Summary | Body fields |
|---|---|---|---|
GET | /admin/config | What this process was started with, and who is asking | — |
GET | /admin/deployment | The FastllmProxy resource running this deployment, and its status | — |
PATCH | /admin/deployment | Change the shape of this deployment: image, replicas, policy, autoscaling | — |
POST | /admin/snapshot/rebuild | Rebuild and republish the snapshot now | — |
GET | /docs | Swagger UI over the spec. The page pulls its bundle from a CDN, so an air-gapped deployment gets an empty page while /openapi.json still works | — |
GET | /health | Per-backend health, in-flight and error counts. Unauthenticated - exposes backend addresses | — |
POST | /health-report | Per-replica backend health. Proxy token only | — |
GET | /healthz | Liveness. Unauthenticated and does no database work, so probing it often costs nothing | — |
GET | /openapi.json | This document. Unauthenticated: a spec you need a session to read is one nobody generates a client from | — |
GET | /snapshot | The flattened routing table a proxy replica polls. Proxy token only - returns decrypted upstream credentials | — |
POST | /usage | Batched usage reporting from a proxy replica. Proxy token only | events |
* optional field
<!-- END GENERATED: endpoints -->Traps
Config changes reach proxies on their snapshot poll, not instantly. If a
change appears in /admin/* but not in behaviour, check the proxy actually
refreshed before assuming the change was wrong.
/health 503 on the gateway means no usable snapshot, not a dead process. A
401 from the gateway means it is healthy and rejecting an unauthenticated
request — that is a successful smoke test, not a failure.
AppState::apply_snapshot is the single write path, and it rebuilds the
routing registry in the same call so the two cannot diverge. Never write the
snapshot cell directly.
The request path performs no I/O. tests/no_io_on_hot_path.rs guards this
and must be extended whenever new work lands there.
© 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-deployment of azrtydxb/Fastllm-proxy.
Open the folder on GitHubat commit 5d53db8
Compare with similar skills
Fastllm Deployment 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 Deployment this skillazrtydxb/Fastllm-proxy | 108 | — | ~727 | Automated safety check: Pass | Apache-2.0 | |
| Tianji Worker Operationsmsgbyte/tianji | 3.1k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Databricks Model Servingdatabricks/databricks-agent-skills | 345 | 1 repos | ~3.4k | Automated safety check: Pass | Custom licence | |
| C4 Containeraiskillstore/marketplace | 433 | 7 repos | ~1.4k | Automated safety check: Pass | None | |
| Azure AI Projects Pyaiskillstore/marketplace | 433 | 4 repos | ~2.1k | Automated safety check: Pass | None | |
| Attio Upgrade Migrationjeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~1k | Automated safety check: Pass | MIT |
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More from azrtydxb/Fastllm-proxy
All 14 skills in this repoFastllm Agents
azrtydxb/Fastllm-proxy
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 Gateway
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…
Fastllm MCP
azrtydxb/Fastllm-proxy
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
azrtydxb/Fastllm-proxy
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
Questions about Fastllm Deployment
What does Fastllm Deployment do?
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 Deployment is an agent skill from azrtydxb/Fastllm-proxy. 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 readiness.
When should I use Fastllm Deployment?
Fastllm Deployment fits situations like: A configuration change has not taken effect; A proxy is serving stale policy; confirm what a running instance actually believes.
How do I install Fastllm Deployment in Claude Code?
Run `npx skills add azrtydxb/Fastllm-proxy --skill fastllm-deployment -a claude-code`. Or copy the skill folder (.claude/skills/fastllm-deployment in azrtydxb/Fastllm-proxy) into .claude/skills/fastllm-deployment in your project. Claude Code loads it when a task matches its description.
How do I install Fastllm Deployment in Codex?
Run `npx skills add azrtydxb/Fastllm-proxy --skill fastllm-deployment -a codex`. Or copy the skill folder (.claude/skills/fastllm-deployment in azrtydxb/Fastllm-proxy) into .agents/skills/fastllm-deployment in your project. Codex loads it when a task matches its description.
Can I use Fastllm Deployment 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-deployment -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-deployment, .gemini/skills/fastllm-deployment, .github/skills/fastllm-deployment and .opencode/skills/fastllm-deployment in your project.
What does Fastllm Deployment need to run?
Going by SKILL.md and its folder, Fastllm Deployment needs the command-line tools its instructions call (curl).
Does Fastllm Deployment 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 Deployment 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 Deployment use?
Fastllm Deployment 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 Deployment use?
About 727 tokens (SKILL.md is roughly 2.9k 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 Deployment?
Skills that share tags, products or a category with Fastllm Deployment: Tianji Worker Operations (msgbyte/tianji, 3.1k stars), Databricks Model Serving (databricks/databricks-agent-skills, 345 stars), C4 Container (aiskillstore/marketplace, 433 stars) and Azure AI Projects Py (aiskillstore/marketplace, 433 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Fastllm Deployment?
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 5, 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.