Agent skill

AI

by butterbase-ai in butterbase-ai/butterbase-skills

A skill your agent uses when calling the app's AI gateway from agent tools — chat completions, embeddings, listing models, configuring defaults or BYOK, reading token/cost usage

MITAuto-check passedAI & LLM Engineering

Install AI

skills CLI

$ npx skills add butterbase-ai/butterbase-skills --skill ai -a claude-code

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

GitHub CLI

$ gh skill install butterbase-ai/butterbase-skills ai --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/butterbase-ai/butterbase-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai .claude/skills/ai && 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 "ai" agent skill from https://github.com/butterbase-ai/butterbase-skills/tree/main/skills/ai into .claude/skills/ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai", 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/butterbase-ai/butterbase-skills/tree/main/skills/ai

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 butterbase-ai/butterbase-skills --skill ai -a codex

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

GitHub CLI

$ gh skill install butterbase-ai/butterbase-skills ai --agent codex

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

Manual copy

$ git clone --depth 1 https://github.com/butterbase-ai/butterbase-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai .agents/skills/ai && 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 "ai" agent skill from https://github.com/butterbase-ai/butterbase-skills/tree/main/skills/ai into .agents/skills/ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai", 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 butterbase-ai/butterbase-skills --skill ai -a cursor

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

GitHub CLI

$ gh skill install butterbase-ai/butterbase-skills ai --agent cursor

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

Manual copy

$ git clone --depth 1 https://github.com/butterbase-ai/butterbase-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai .cursor/skills/ai && 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 "ai" agent skill from https://github.com/butterbase-ai/butterbase-skills/tree/main/skills/ai into .cursor/skills/ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai", 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/butterbase-ai/butterbase-skills.git --path skills/ai

--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 butterbase-ai/butterbase-skills --skill ai -a gemini-cli

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

GitHub CLI

$ gh skill install butterbase-ai/butterbase-skills ai --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/butterbase-ai/butterbase-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai .gemini/skills/ai && 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 "ai" agent skill from https://github.com/butterbase-ai/butterbase-skills/tree/main/skills/ai into .gemini/skills/ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai", 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 butterbase-ai/butterbase-skills ai

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 butterbase-ai/butterbase-skills --skill ai -a github-copilot

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

Manual copy

$ git clone --depth 1 https://github.com/butterbase-ai/butterbase-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai .github/skills/ai && 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 "ai" agent skill from https://github.com/butterbase-ai/butterbase-skills/tree/main/skills/ai into .github/skills/ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai", 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 butterbase-ai/butterbase-skills --skill ai -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 butterbase-ai/butterbase-skills ai --agent opencode

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

Manual copy

$ git clone --depth 1 https://github.com/butterbase-ai/butterbase-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai .opencode/skills/ai && 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 "ai" agent skill from https://github.com/butterbase-ai/butterbase-skills/tree/main/skills/ai into .opencode/skills/ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai", 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: ai
GitHub stars: 534
Token cost: ~1.1k tokens
SKILL.md length: 385 words
Files: 1
Skills in repo: 39
Repo updated: Oct 5, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

A skill your agent uses when calling the app's AI gateway from agent tools — chat completions, embeddings, listing models, configuring defaults or BYOK, reading token/cost usage

Works in 8 steps: Chat → Embed → List models → …
Calling the apps AI gateway from agent tools — chat completions
SKILL.md covers 1. Chat, 2. Embed, 3. List models and 4. Configure, plus 4 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

AI is an agent skill from butterbase-ai/butterbase-skills. Use when calling the app's AI gateway from agent tools — chat completions, embeddings, listing models, configuring defaults or BYOK, reading token/cost usage

Its SKILL.md is about 1.1k 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 Embeddings, LLM API integration and LLM cost and token optimization. The repository describes itself as: Plugin for Butterbase.ai. The licence is MIT.

When your agent uses it

Calling the apps AI gateway from agent tools — chat completions
Configuring defaults
Reading token/cost usage

Example prompts

“/ai”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

Chat
Embed
List models
Configure
Usage
Common pitfalls
What this skill does NOT cover
Decisions (typed classification)

What it can do on your machine

Read from SKILL.md and the folder at commit aa8ae69. 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
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.

Context cost

AI loads about 1.1k tokens when it runs. Until then it costs about 40 tokens; SKILL.md has 385 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~40
When it runs · the whole SKILL.md, loaded when a task matches: ~1.1k

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 butterbase-ai/butterbase-skills at commit aa8ae69, republished under its MIT licence (© butterbase-ai). 385 words, ~1,112 tokens.

Download SKILL.mdSave it as .claude/skills/ai/SKILL.md (or your agent's skills folder).

name: ai
description: Use when calling the app's AI gateway from agent tools — chat completions, embeddings, listing models, configuring defaults or BYOK, reading token/cost usage

Butterbase AI Gateway

Every app has an LLM gateway with chat, embeddings, model listing, configuration, and usage reporting. One umbrella tool: manage_ai.

Action	What it does	Returns
`chat`	Synchronous chat completion (no streaming)	OpenAI-shaped `{ choices: [...] }`
`embed`	Vector embeddings for string or string[]	OpenAI-shaped `{ data: [{ embedding: [...] }] }`
`list_models`	Available models with capabilities	`{ models: AiModel[] }`
`get_config`	Current AI config (default model, BYOK key flag, etc.)	`AiConfig`
`update_config`	Set defaults, allowed models, max tokens, BYOK	`AiConfig`
`get_usage`	Token + cost aggregate over a window	usage record

1. Chat

manage_ai({
  action: "chat",
  app_id,
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user",   content: "What's RAG?" }
  ],
  model: "openai/gpt-4o-mini",     // optional — falls back to app's default
  temperature: 0.2,                // optional
  max_tokens: 500                  // optional
})

This action sets stream: false deliberately — agent tools don't stream. If you need partial-token deltas, drive the SDK's ai.chatStream(…) from inside a function or DO instead.

messages[].content can be a string or an array of content parts ({ type: "text", text }, { type: "image_url", image_url: {...} }, { type: "video_url", video_url: {...} }).

2. Embed

manage_ai({
  action: "embed",
  app_id,
  input: "hello world",            // or ["a", "b", "c"]
  model: "openai/text-embedding-3-small",   // optional
  encoding_format: "float"          // or "base64"
})

3. List models

manage_ai({ action: "list_models", app_id })
// → { models: [{ id, provider, capabilities: ["chat", "embed", ...], context_window, pricing }, ...] }

Use this to discover what the app can call — capabilities + context window matter when picking a model.

4. Configure

manage_ai({
  action: "update_config",
  app_id,
  config: {
    defaultModel: "openai/gpt-4o-mini",
    allowedModels: ["openai/gpt-4o-mini", "anthropic/claude-haiku-4-5"],
    maxTokensPerRequest: 4000,
    byokKey: "..." // optional — rotates the customer-supplied OpenRouter / Anthropic key
  }
})

maxTokensPerRequest is server-clamped to 1–100000.
allowedModels is a whitelist — empty means all models the provider exposes.
Setting byokKey switches the app to route through that customer key. Clear it by passing byokKey: "" (returns to platform pool).

5. Usage

manage_ai({
  action: "get_usage",
  app_id,
  startDate: "2026-05-01",
  endDate:   "2026-05-31"
})

Returns aggregate token counts + cost. Useful for billing reconciliation, spending-cap diagnostics, and showing dashboards.

Show full SKILL.md (180 more words)Show less

6. Common pitfalls

Trying to stream from a tool — manage_ai is synchronous. Use the SDK inside a function for streamed deltas.
Sending stream: true in the body — the tool ignores it; always wired to false.
Hardcoding model — better to omit, let the app's defaultModel win, and surface that knob via update_config.
Skipping list_models before suggesting one — model availability shifts; verify before recommending.

7. What this skill does NOT cover

Streaming chat — use the SDK (ai.chatStream) inside a function or DO.
Vector storage / retrieval — see butterbase-skills:rag-dev (RAG collections wrap embeddings + search together).
AI in deployed functions — they import @butterbase/sdk and call client.ai.* directly; no MCP needed at runtime.

8. Decisions (typed classification)

For routing, classification, moderation or scoring, where code needs a choice / yes-no / score with probabilities, use manage_ai action: "decide" (SDK ai.decide) with a decision model (default typesafe/jev-1.13) instead of asking a chat model for JSON. It is cheaper, faster and returns typed probabilities. Full reference: butterbase_docs topic ai, "Decision models".

If a docs/butterbase/00-state.md exists in the working directory, prefer invoking via /butterbase-skills:journey-ai so the journey orchestrator stays in sync.

Files

Just SKILL.md in skills/ai of butterbase-ai/butterbase-skills.

Open the folder on GitHubat commit aa8ae69

Compare with similar skills

AI 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.

AI compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
AI this skillbutterbase-ai/butterbase-skills	534	—	~1.1k	Automated safety check: Pass	MIT	4 days ago
Fastllm Gatewayazrtydxb/Fastllm-proxy	108	—	~926	Automated safety check: Pass	Apache-2.0	4 days ago
LLM Cost Optimizationsickn33/agentic-awesome-skills	47k	1 repos	~2.5k	Automated safety check: Pass	MIT	today
Unified LLM APIPrism-Shadow/penguin-harness	2.5k	—	~6.7k	Automated safety check: Pass	Apache-2.0	2 days ago
Gemini Live APIgoogle/skills	21k	—	~2.5k	Automated safety check: Notes	Apache-2.0	today
RAG Architectalirezarezvani/claude-skills	28k	—	~1.1k	Automated safety check: Pass	MIT	1 mo ago

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More from butterbase-ai/butterbase-skills

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Build App
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Contributing
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Debug Rls
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Deploy Frontend
butterbase-ai/butterbase-skills
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Durable Objects
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Questions about AI

What does AI do?

A skill your agent uses when calling the app's AI gateway from agent tools — chat completions, embeddings, listing models, configuring defaults or BYOK, reading token/cost usage. AI is an agent skill from butterbase-ai/butterbase-skills.

When should I use AI?

AI fits situations like: calling the apps AI gateway from agent tools — chat completions; configuring defaults; reading token/cost usage.

How do I install AI in Claude Code?

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

How do I install AI in Codex?

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

Can I use AI 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 butterbase-ai/butterbase-skills --skill ai -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai, .gemini/skills/ai, .github/skills/ai and .opencode/skills/ai in your project.

What does AI need to run?

SKILL.md names no scripts, command-line tools or credentials: AI is instructions for the agent only.

Does AI 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 AI 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 AI use?

AI 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 AI use?

About 1.1k tokens (SKILL.md is roughly 4.4k 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 AI?

Skills that share tags, products or a category with AI: Fastllm Gateway (azrtydxb/Fastllm-proxy, 108 stars), LLM Cost Optimization (sickn33/agentic-awesome-skills, 47k stars), Unified LLM API (Prism-Shadow/penguin-harness, 2.5k stars) and Gemini Live API (google/skills, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains AI?

butterbase-ai (a GitHub organization) maintains it in butterbase-ai/butterbase-skills, which has 534 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on October 5, 2026.

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

Install AI

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Butterbase AI Gateway

1. Chat

2. Embed

3. List models

4. Configure

5. Usage

6. Common pitfalls

7. What this skill does NOT cover

8. Decisions (typed classification)

Files

Compare with similar skills

Similar skills

More from butterbase-ai/butterbase-skills

Related

Questions about AI