Deploy Fullstack Vercel
vellum-ai/vellum-assistant
Build and deploy a full-stack app (React frontend + Python/FastAPI backend) or a Vellum app to Vercel as a serverless demo with seeded data
Configure fastapi ml endpoint operations. An agent skill from jeremylongshore/tons-of-skills-marketplace.
Install Fastapi ML Endpoint
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill fastapi-ml-endpoint -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace fastapi-ml-endpoint --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/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/08-ml-deployment/fastapi-ml-endpoint .claude/skills/fastapi-ml-endpoint && 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 "fastapi-ml-endpoint" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/08-ml-deployment/fastapi-ml-endpoint into .claude/skills/fastapi-ml-endpoint/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastapi-ml-endpoint", 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/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/08-ml-deployment/fastapi-ml-endpointType 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 jeremylongshore/tons-of-skills-marketplace --skill fastapi-ml-endpoint -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace fastapi-ml-endpoint --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/08-ml-deployment/fastapi-ml-endpoint .agents/skills/fastapi-ml-endpoint && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "fastapi-ml-endpoint" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/08-ml-deployment/fastapi-ml-endpoint into .agents/skills/fastapi-ml-endpoint/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastapi-ml-endpoint", 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 jeremylongshore/tons-of-skills-marketplace --skill fastapi-ml-endpoint -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace fastapi-ml-endpoint --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/08-ml-deployment/fastapi-ml-endpoint .cursor/skills/fastapi-ml-endpoint && 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 "fastapi-ml-endpoint" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/08-ml-deployment/fastapi-ml-endpoint into .cursor/skills/fastapi-ml-endpoint/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastapi-ml-endpoint", 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/jeremylongshore/tons-of-skills-marketplace.git --path skills/08-ml-deployment/fastapi-ml-endpoint--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 jeremylongshore/tons-of-skills-marketplace --skill fastapi-ml-endpoint -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace fastapi-ml-endpoint --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/08-ml-deployment/fastapi-ml-endpoint .gemini/skills/fastapi-ml-endpoint && 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 "fastapi-ml-endpoint" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/08-ml-deployment/fastapi-ml-endpoint into .gemini/skills/fastapi-ml-endpoint/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastapi-ml-endpoint", 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 jeremylongshore/tons-of-skills-marketplace fastapi-ml-endpointInstalls 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 jeremylongshore/tons-of-skills-marketplace --skill fastapi-ml-endpoint -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/08-ml-deployment/fastapi-ml-endpoint .github/skills/fastapi-ml-endpoint && 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 "fastapi-ml-endpoint" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/08-ml-deployment/fastapi-ml-endpoint into .github/skills/fastapi-ml-endpoint/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastapi-ml-endpoint", 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 jeremylongshore/tons-of-skills-marketplace --skill fastapi-ml-endpoint -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace fastapi-ml-endpoint --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/08-ml-deployment/fastapi-ml-endpoint .opencode/skills/fastapi-ml-endpoint && 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 "fastapi-ml-endpoint" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/08-ml-deployment/fastapi-ml-endpoint into .opencode/skills/fastapi-ml-endpoint/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fastapi-ml-endpoint", 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
fastapi-ml-endpoint- GitHub stars
- 2.8k
- Token cost
- ~561 tokens
- SKILL.md length
- 196 words
- Files
- 1
- Skills in repo
- 3,342
- Repo updated
- First seen
- Licence
- MIT
At a glance
Configure fastapi ml endpoint operations. An agent skill from jeremylongshore/tons-of-skills-marketplace.
- Works in 4 steps: Provides step-by-step guidance for… → Follows industry best practices and… → Generates production-ready code and… → …
- : fastapi ml endpoint
- SKILL.md covers Overview, When to Use, Instructions and Examples, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Fastapi ML Endpoint is an agent skill from jeremylongshore/tons-of-skills-marketplace. Configure fastapi ml endpoint operations. Auto-activating skill for ML Deployment. Triggers on: fastapi ml endpoint, fastapi ml endpoint Part of the ML Deployment skill category. Use when working with APIs or building integrations. Trigger with phrases like "fastapi ml endpoint", "fastapi endpoint", "fastapi".
Its SKILL.md is about 560 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Designed for Claude Code
It sits in Backend & APIs, covering Backend development and Deployment. It works with FastAPI. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.
When your agent uses it
- : fastapi ml endpoint
- Fastapi ml endpoint Part of the ML Deployment skill category
- Working with APIs
- Building integrations
Example prompts
- “fastapi ml endpoint”
- “fastapi endpoint”
- “fastapi”
- “/fastapi-ml-endpoint”
Requirements
- Compatibility (from SKILL.md): Designed for Claude Code
- Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(cmd:*), Grep
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Provides step-by-step guidance for fastapi ml endpoint
- Follows industry best practices and patterns
- Generates production-ready code and configurations
- Validates outputs against common standards
What it can do on your machine
Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditBash(cmd:*)Grep
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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.
Compatibility
Designed for Claude Code
From compatibility in the SKILL.md frontmatter.
Context cost
Fastapi ML Endpoint loads about 561 tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 196 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 jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 196 words, ~561 tokens.
Download SKILL.mdSave it as
.claude/skills/fastapi-ml-endpoint/SKILL.md (or your agent's skills folder).- name
- fastapi-ml-endpoint
- description
- Configure fastapi ml endpoint operations. Auto-activating skill for ML Deployment. Triggers on: fastapi ml endpoint, fastapi ml endpoint Part of the ML Deployment skill category. Use when working with APIs or building integrations. Trigger with phrases like "fastapi ml endpoint", "fastapi endpoint", "fastapi".
- allowed-tools
- Read, Write, Edit, Bash(cmd:*), Grep
- compatibility
- Designed for Claude Code
- version
- 1.0.0
- license
- MIT
- author
- Jeremy Longshore <jeremy@intentsolutions.io>
- tags
- ai, mlops
Fastapi Ml Endpoint
Overview
This skill provides automated assistance for fastapi ml endpoint tasks within the ML Deployment domain.
When to Use
This skill activates automatically when you:
- Mention "fastapi ml endpoint" in your request
- Ask about fastapi ml endpoint patterns or best practices
- Need help with machine learning deployment skills covering model serving, mlops pipelines, monitoring, and production optimization.
Instructions
- Provides step-by-step guidance for fastapi ml endpoint
- Follows industry best practices and patterns
- Generates production-ready code and configurations
- Validates outputs against common standards
Examples
Example: Basic Usage Request: "Help me with fastapi ml endpoint" Result: Provides step-by-step guidance and generates appropriate configurations
Prerequisites
- Relevant development environment configured
- Access to necessary tools and services
- Basic understanding of ml deployment concepts
Output
- Generated configurations and code
- Best practice recommendations
- Validation results
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |
Resources
- Official documentation for related tools
- Best practices guides
- Community examples and tutorials
Related Skills
Part of the ML Deployment skill category. Tags: mlops, serving, inference, monitoring, production
© jeremylongshore, MIT. 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 skills/08-ml-deployment/fastapi-ml-endpoint of jeremylongshore/tons-of-skills-marketplace.
Open the folder on GitHubat commit cfae287
Compare with similar skills
Fastapi ML Endpoint 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 |
|---|---|---|---|---|---|---|
| Fastapi ML Endpoint this skilljeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~561 | Automated safety check: Pass | MIT | |
| Deploy Fullstack Vercelvellum-ai/vellum-assistant | 1.4k | — | ~2.8k | Automated safety check: Pass | MIT | |
| AI ServerOpentrons/opentrons | 523 | — | ~2.5k | Automated safety check: Notes | Apache-2.0 | |
| Model Deploymentsecondsky/claude-skills | 227 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Fastcrudbenavlabs/fastcrud | 1.6k | — | ~5k | Automated safety check: Pass | MIT | |
| FastapiOpen-TutorAi/open-tutor-ai-CE | 108 | 2 repos | ~2.6k | Automated safety check: Pass | BSD-3-Clause |
Similar skills
AI Server
Opentrons/opentrons
Conventions for the opentrons-ai-server FastAPI service — project structure, uv dependency management, settings, testing, Docker, and deployment.
Model Deployment
secondsky/claude-skills
Deploy ML models with FastAPI, Docker, Kubernetes. An agent skill from secondsky/claude-skills.
Fastcrud
benavlabs/fastcrud
A skill your agent uses when building or modifying CRUD endpoints with FastCRUD (the fastcrud PyPI package) in a FastAPI project — covers FastCRUD, crudrouter, EndpointCreator, FilterConfig…
Fastapi
Open-TutorAi/open-tutor-ai-CE
FastAPI best practices and conventions. An agent skill from Open-TutorAi/open-tutor-ai-CE.
API Surface Review
polarsource/polar
Review changes to Polar's API contract — Pydantic schemas, FastAPI endpoints, OpenAPI output and the generated SDKs.
More from jeremylongshore/tons-of-skills-marketplace
All 3,342 skills in this repoPerforming Security Code Review
jeremylongshore/tons-of-skills-marketplace
Execute this skill enables AI assistant to conduct a security-focused code review using the security-agent plugin.
Adapting Transfer Learning Models
jeremylongshore/tons-of-skills-marketplace
Build this skill automates the adaptation of pre-trained machine learning models using transfer learning techniques.
Agent Context Loader
jeremylongshore/tons-of-skills-marketplace
Execute proactive auto-loading: automatically detects and loads agents.md files.
Aggregating Performance Metrics
jeremylongshore/tons-of-skills-marketplace
Aggregate and centralize performance metrics from applications, systems, databases, caches, and services.
Analyzing Capacity Planning
jeremylongshore/tons-of-skills-marketplace
Execute this skill enables AI assistant to analyze capacity requirements and plan for future growth.
Analyzing Database Indexes
jeremylongshore/tons-of-skills-marketplace
Process use when you need to work with database indexing. An agent skill from jeremylongshore/tons-of-skills-marketplace.
Related
Works with
Categories
Questions about Fastapi ML Endpoint
What does Fastapi ML Endpoint do?
Configure fastapi ml endpoint operations. An agent skill from jeremylongshore/tons-of-skills-marketplace. Fastapi ML Endpoint is an agent skill from jeremylongshore/tons-of-skills-marketplace. Configure fastapi ml endpoint operations.
When should I use Fastapi ML Endpoint?
Fastapi ML Endpoint fits situations like: : fastapi ml endpoint; fastapi ml endpoint Part of the ML Deployment skill category; working with APIs; building integrations.
How do I install Fastapi ML Endpoint in Claude Code?
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill fastapi-ml-endpoint -a claude-code`. Or copy the skill folder (skills/08-ml-deployment/fastapi-ml-endpoint in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/fastapi-ml-endpoint in your project. Claude Code loads it when a task matches its description.
How do I install Fastapi ML Endpoint in Codex?
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill fastapi-ml-endpoint -a codex`. Or copy the skill folder (skills/08-ml-deployment/fastapi-ml-endpoint in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/fastapi-ml-endpoint in your project. Codex loads it when a task matches its description.
Can I use Fastapi ML Endpoint 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 jeremylongshore/tons-of-skills-marketplace --skill fastapi-ml-endpoint -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fastapi-ml-endpoint, .gemini/skills/fastapi-ml-endpoint, .github/skills/fastapi-ml-endpoint and .opencode/skills/fastapi-ml-endpoint in your project.
What does Fastapi ML Endpoint need to run?
SKILL.md names no scripts, command-line tools or credentials: Fastapi ML Endpoint is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(cmd:*), Grep. Compatibility (from SKILL.md): Designed for Claude Code.
Does Fastapi ML Endpoint access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Fastapi ML Endpoint 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 Fastapi ML Endpoint use?
Fastapi ML Endpoint is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Fastapi ML Endpoint use?
About 561 tokens (SKILL.md is roughly 2.2k 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 Fastapi ML Endpoint?
Skills that share tags, products or a category with Fastapi ML Endpoint: Deploy Fullstack Vercel (vellum-ai/vellum-assistant, 1.4k stars), AI Server (Opentrons/opentrons, 523 stars), Model Deployment (secondsky/claude-skills, 227 stars) and Fastcrud (benavlabs/fastcrud, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Fastapi ML Endpoint?
jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.
Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.