Gemini API
google/skills
A skill your agent uses when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform.
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK.
Install Vertex AI API Dev
$ npx skills add JetBrains/skills --skill vertex-ai-api-dev -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install JetBrains/skills vertex-ai-api-dev --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/JetBrains/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/vertex-ai-api-dev .claude/skills/vertex-ai-api-dev && 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 "vertex-ai-api-dev" agent skill from https://github.com/JetBrains/skills/tree/main/vertex-ai-api-dev into .claude/skills/vertex-ai-api-dev/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vertex-ai-api-dev", 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/JetBrains/skills/tree/main/vertex-ai-api-devType 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 JetBrains/skills --skill vertex-ai-api-dev -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install JetBrains/skills vertex-ai-api-dev --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JetBrains/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/vertex-ai-api-dev .agents/skills/vertex-ai-api-dev && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "vertex-ai-api-dev" agent skill from https://github.com/JetBrains/skills/tree/main/vertex-ai-api-dev into .agents/skills/vertex-ai-api-dev/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vertex-ai-api-dev", 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 JetBrains/skills --skill vertex-ai-api-dev -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install JetBrains/skills vertex-ai-api-dev --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JetBrains/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/vertex-ai-api-dev .cursor/skills/vertex-ai-api-dev && 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 "vertex-ai-api-dev" agent skill from https://github.com/JetBrains/skills/tree/main/vertex-ai-api-dev into .cursor/skills/vertex-ai-api-dev/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vertex-ai-api-dev", 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/JetBrains/skills.git --path vertex-ai-api-dev--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 JetBrains/skills --skill vertex-ai-api-dev -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install JetBrains/skills vertex-ai-api-dev --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JetBrains/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/vertex-ai-api-dev .gemini/skills/vertex-ai-api-dev && 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 "vertex-ai-api-dev" agent skill from https://github.com/JetBrains/skills/tree/main/vertex-ai-api-dev into .gemini/skills/vertex-ai-api-dev/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vertex-ai-api-dev", 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 JetBrains/skills vertex-ai-api-devInstalls 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 JetBrains/skills --skill vertex-ai-api-dev -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/JetBrains/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/vertex-ai-api-dev .github/skills/vertex-ai-api-dev && 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 "vertex-ai-api-dev" agent skill from https://github.com/JetBrains/skills/tree/main/vertex-ai-api-dev into .github/skills/vertex-ai-api-dev/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vertex-ai-api-dev", 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 JetBrains/skills --skill vertex-ai-api-dev -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install JetBrains/skills vertex-ai-api-dev --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JetBrains/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/vertex-ai-api-dev .opencode/skills/vertex-ai-api-dev && 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 "vertex-ai-api-dev" agent skill from https://github.com/JetBrains/skills/tree/main/vertex-ai-api-dev into .opencode/skills/vertex-ai-api-dev/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vertex-ai-api-dev", 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
vertex-ai-api-dev- GitHub stars
- 363
- Used in
- 1 other repo
- Token cost
- ~2.4k tokens
- SKILL.md length
- 660 words
- Files
- 10 (incl. references)
- Skills in repo
- 79
- Repo updated
- First seen
- Licence
- None found
At a glance
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK.
- The user asks about using Gemini in an enterprise environment
- SKILL.md covers Core Directives, SDKs, Authentication & Configuration and Models, plus 3 more sections
- Calls pip, npm and go; needs GOOGLE_API_KEY
- Explicitly mentions Vertex AI
What it does
Vertex AI API Dev is an agent skill from JetBrains/skills, published by the product's own GitHub organization. Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI. Covers SDK usage (Python, JS/TS, Go, Java, C), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files (for example `references/advanced_features.md`, `references/bounding_box.md` and `references/embeddings.md`). Compatibility notes: Requires active Google Cloud credentials and Vertex AI API enabled.
It sits in AI & LLM Engineering, covering LLM API integration and Caching. It works with Vertex AI, C#, Java and Python. The repository describes itself as: Curated agent skills collection verified by JetBrains.
When your agent uses it
- The user asks about using Gemini in an enterprise environment
- Explicitly mentions Vertex AI
Example prompts
- “Use the vertex-ai-api-dev skill to guide the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK”
- “/vertex-ai-api-dev”
Requirements
- Python 3
- Node.js
- A credential in GOOGLE_API_KEY
- Compatibility (from SKILL.md): Requires active Google Cloud credentials and Vertex AI API enabled.
What it can do on your machine
Read from SKILL.md and the folder at commit e0f258b. 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:
pipnpmgodotnet
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
docs.cloud.google.comcloud.google.comcentral.sonatype.comgithub.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
GOOGLE_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compatibility
Requires active Google Cloud credentials and Vertex AI API enabled.
From compatibility in the SKILL.md frontmatter.
Context cost
Vertex AI API Dev loads about 2.4k tokens when it runs, and up to ~7.4k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 660 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
Without a licence we can't republish the file, so here is its outline and opening line. It has 660 words (~2,414 tokens).
“Access Google's most advanced AI models built for enterprise use cases using the Gemini API in Vertex AI.”
- name
- vertex-ai-api-dev
- compatibility
- Requires active Google Cloud credentials and Vertex AI API enabled.
- metadata.short-description
- Use Gemini on Vertex AI
- metadata.author
- Google Gemini
- metadata.source
- https://github.com/google-gemini/gemini-skills/tree/main/skills/vertex-ai-api-dev
Files
SKILL.md and 9 other files (references) in vertex-ai-api-dev of JetBrains/skills.
- SKILL.md
- references/advanced_features.md
- references/bounding_box.md
- references/embeddings.md
- references/live_api.md
- references/media_generation.md
- references/model_tuning.md
- references/safety.md
- references/structured_and_tools.md
- references/text_and_multimodal.md
Open the folder on GitHubat commit e0f258b
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in JetBrains/skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Vertex AI API Dev 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 |
|---|---|---|---|---|---|---|
| Vertex AI API Dev this skillJetBrains/skills | 363 | 1 repos | ~2.4k | Automated safety check: Pass | None | |
| Gemini APIgoogle/skills | 21k | 3 repos | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Gemini API DevAyuilos/Miffan | 182 | 1 repos | ~1.4k | Automated safety check: Pass | AGPL-3.0 | |
| Claude API Developmentwarpdotdev/warp | 65k | 3 repos | ~8.2k | Automated safety check: Pass | Apache-2.0 | |
| Google Genai SDK Pythoncnemri/google-genai-skills | 127 | — | ~422 | Automated safety check: Pass | MIT | |
| Gemini API Devaiskillstore/marketplace | 430 | 3 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about Vertex AI API Dev
What does Vertex AI API Dev do?
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK. Vertex AI API Dev is an agent skill from JetBrains/skills, published by the product's own GitHub organization. Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK.
When should I use Vertex AI API Dev?
Vertex AI API Dev fits situations like: the user asks about using Gemini in an enterprise environment; explicitly mentions Vertex AI.
How do I install Vertex AI API Dev in Claude Code?
Run `npx skills add JetBrains/skills --skill vertex-ai-api-dev -a claude-code`. Or copy the skill folder (vertex-ai-api-dev in JetBrains/skills) into .claude/skills/vertex-ai-api-dev in your project. Claude Code loads it when a task matches its description.
How do I install Vertex AI API Dev in Codex?
Run `npx skills add JetBrains/skills --skill vertex-ai-api-dev -a codex`. Or copy the skill folder (vertex-ai-api-dev in JetBrains/skills) into .agents/skills/vertex-ai-api-dev in your project. Codex loads it when a task matches its description.
Can I use Vertex AI API Dev 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 JetBrains/skills --skill vertex-ai-api-dev -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vertex-ai-api-dev, .gemini/skills/vertex-ai-api-dev, .github/skills/vertex-ai-api-dev and .opencode/skills/vertex-ai-api-dev in your project.
What does Vertex AI API Dev need to run?
Going by SKILL.md and its folder, Vertex AI API Dev needs the command-line tools its instructions call (pip, npm, go and dotnet) and credentials named GOOGLE_API_KEY. Our summary lists: Python 3; Node.js; A credential in GOOGLE_API_KEY. Compatibility (from SKILL.md): Requires active Google Cloud credentials and Vertex AI API enabled..
Does Vertex AI API Dev access the network?
SKILL.md names 4 domains. As links in the text: docs.cloud.google.com, cloud.google.com, central.sonatype.com and github.com. This is read from the text; nothing was executed.
Is Vertex AI API Dev 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 Vertex AI API Dev use?
No licence was found for Vertex AI API Dev or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Vertex AI API Dev use?
About 2.4k tokens (SKILL.md is roughly 9.7k 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 5k tokens, read only when the agent opens those files.
What are the alternatives to Vertex AI API Dev?
Skills that share tags, products or a category with Vertex AI API Dev: Gemini API (google/skills, 21k stars), Gemini API Dev (Ayuilos/Miffan, 182 stars), Claude API Development (warpdotdev/warp, 65k stars) and Google Genai SDK Python (cnemri/google-genai-skills, 127 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Vertex AI API Dev?
JetBrains (a GitHub organization, an official publisher) maintains it in JetBrains/skills, which has 363 GitHub stars. The repository holds 79 skills in this directory. The repository was last updated on June 29, 2026.
Source: JetBrains/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.