Tools & Skills

Tools are functions the agent calls on its own during a response - reading a file, running a shell command, doing a web search. You see each tool call as a card in the message stream showing what ran and what came back. In Ask mode, writes and shell commands pause for your approval before executing.

Skills (/commit, /debug, etc.) are structured workflows you trigger explicitly. They load a pre-written policy into the agent's context that shapes how it approaches the task - which tools it's allowed to use, what order to do things in, and when to stop and ask you. You invoke them with a slash command in any AI panel.

Client-side slash commands (/help, /clear, /compact, /mode, /preview, /map, /export) are handled entirely in the app - nothing goes to the LLM.

The shell tool runs commands in your project directory: git operations, package managers, test runners, compilers, linters - anything you'd run in a terminal.

Every command is classified into one of three tiers before it runs:

• SAFE (auto-approve in Act mode): ls, cat, git status, and similar read-only commands.
• MODERATE (brief confirmation): npm install, git commit, and similar.
• DANGEROUS (full approval dialog): rm, chmod, git push, curl, and similar.

In Ask mode, shell commands always show an approval card regardless of tier - there is no auto-approve timeout.

After every execution, output is scanned for 13 credential patterns: SSH private keys, AWS AKIA* keys, GitHub ghp_* PATs, OpenAI sk-* keys, JWTs, and high-entropy base64 strings over 40 chars.

Air-gap mode blocks all network-touching shell commands: curl, wget, ssh, git clone/push/pull, npm install, pip install, docker pull.

Both web tools are blocked entirely in air-gap mode.

These two tools work together when Bodega is interacting with a live web app in the Preview tab.

preview_interaction lets the agent drive the Preview tab (an embedded browser). Five actions:

• screenshot - captures a PNG and returns an img_XXXXXXXX handle
• navigate - loads a localhost URL (only localhost accepted)
• click - clicks an element by CSS selector (approval-gated by default)
• getDom - returns outerHTML for a selector (output capped at 8,000 chars)
• getConsoleErrors - returns sanitized JS console errors

vision_query takes an image_id from a prior screenshot and a plain-English question (max 500 chars), sends both to your configured Vision Language Model, and returns a text answer. This is how a text-only loop driver (e.g., Claude) can "see" the screen.

To use vision features: configure a VLM in Settings → Models → Vision Model, and have the Preview tab open with a dev server running.

Skills load a policy into the agent that controls how it approaches the task. Type / in any AI panel to see autocomplete.

These are handled entirely in the app - nothing goes to the LLM.

Custom agents let you define named profiles with a tailored system prompt, an optional pinned model, a tool allowlist, and an iteration cap.

To create a custom agent:

1. Go to Settings → Custom Agents
2. Fill in: Name (required, max 100 chars), System Prompt (required, max 6,000 chars), and optionally Description, a pinned Model, Tool Allowlist, Read-only filesystem, and Max Iterations (1–50)
3. Leave the tool allowlist empty to allow all tools. Add specific tools to restrict what the agent can call.
4. Save.

To use a custom agent:

1. Open Code Mode and find the Agent panel
2. In the Agent panel header, click the profile picker dropdown (robot icon, shows "Default" when none selected). The picker is hidden if you have no custom agents.
3. Select a custom agent. The next message you send applies that profile.
4. Switch back to Default to remove the profile.

If a selected agent is deleted, the picker falls back to Default automatically. Tool allowlists are validated against the live tool registry - invalid tool names are rejected at create time.

Permission mode (ask/plan/act) and sandbox rules are global settings, not agent-derived.

The ACP (Agent Client Protocol) server lets external coding agents run as Fleet members inside Bodega. Supported agents: Gemini CLI, Claude Code, Codex, and Cursor.

Configure at Settings → ACP Agents. What each one needs:

• Gemini CLI - GEMINI_API_KEY and @google/gemini-cli installed globally
• Claude Code - ANTHROPIC_API_KEY and @zed-industries/claude-code-acp installed
• Codex - OPENAI_API_KEY and @zed-industries/codex-acp installed
• Cursor - cursor-agent CLI installed and cursor-agent login run once (subscription auth, no API key)

Once configured, ACP agents appear as Fleet session options. Communication is NDJSON-RPC over stdin/stdout - Bodega spawns the agent as a child process and routes prompts through the ACP session protocol.

What ACP agents can and can't do:

• File system and shell access routes through Bodega's own tools - sandbox and air-gap rules still apply
• ACP agents do not go through QEL verification - they show an "external - not QEL-verified" badge
• Blocked entirely in air-gap mode - enabling air-gap kills any running ACP subprocesses

When using llama.cpp as your embeddings provider, Bodega can manage the embedding server process automatically - separate from the chat server (port 8080), running on port 8081 by default.

To set it up:

1. Install an embedding-capable GGUF first: go to Models → llama.cpp → Discover and download a model such as nomic-embed-text or a bge model
2. Go to Settings → Knowledge → Search & Embeddings (or Settings → Models → Codebase Embeddings)
3. Set provider to llama.cpp
4. Enable the "Let Bodega manage the embedding server" toggle
5. In the GGUF dropdown, select an installed model (the dropdown only shows models from your llama.cpp library)
6. Optionally set a custom port (default: 8081)

The embedding server starts with the --embedding flag and is fully independent of the chat server. If you'd rather manage the process yourself, leave the toggle off and type the path manually.

The Review button in the Git panel runs an AI code review against your current git diff - the "review before I commit" case. It uses your configured LLM provider, so it works fully locally.

To use it:

1. Make changes to your project files (staged, unstaged, or both)
2. Open the Git panel in Code Mode (Activity Bar → git icon)
3. Click Review (next to the Generate commit message button)
4. The review result appears inline as a markdown block in the Git panel

If the working tree is clean, the review falls back to comparing the branch against its base (the PR-scope view). Large diffs are clipped and a truncation note is appended.

This is separate from the /review skill. The /review skill reads source files and runs a code quality analysis. The Git panel Review button reads the git diff and focuses on what changed.