Hooks Reference

This document provides the technical specification for Gemini CLI hooks, including the JSON schemas for input and output, exit code behaviors, and the stable model API.

Communication Protocol

Hooks communicate with Gemini CLI via standard streams and exit codes:

• Input: Gemini CLI sends a JSON object to the hook’s stdin.
• Output: The hook sends a JSON object (or plain text) to stdout.
• Exit Codes: Used to signal success or blocking errors.

Exit Code Behavior

Exit Code	Meaning	Behavior
0	Success	stdout is parsed as JSON. If parsing fails, it’s treated as a systemMessage.
2	Blocking Error	Interrupts the current operation. stderr is shown to the agent (for tool events) or the user.
Other	Warning	Execution continues. stderr is logged as a non-blocking warning.

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Input Schema (stdin)

Every hook receives a base JSON object. Extra fields are added depending on the specific event.

Base Fields (All Events)

Field	Type	Description
session_id	string	Unique identifier for the current CLI session.
transcript_path	string	Path to the session’s JSON transcript (if available).
cwd	string	The current working directory.
hook_event_name	string	The name of the firing event (e.g., BeforeTool).
timestamp	string	ISO 8601 timestamp of the event.

Event-Specific Fields

Tool Events (BeforeTool, AfterTool)

• tool_name: (string) The internal name of the tool (e.g., write_file, run_shell_command).
• tool_input: (object) The arguments passed to the tool.
• tool_response: (object, AfterTool only) The raw output from the tool execution.

Agent Events (BeforeAgent, AfterAgent)

• prompt: (string) The user’s submitted prompt.
• prompt_response: (string, AfterAgent only) The final response text from the model.
• stop_hook_active: (boolean, AfterAgent only) Indicates if a stop hook is already handling a continuation.

Model Events (BeforeModel, AfterModel, BeforeToolSelection)

• llm_request: (LLMRequest) A stable representation of the outgoing request. See Stable Model API.
• llm_response: (LLMResponse, AfterModel only) A stable representation of the incoming response.

Session & Notification Events

• source: (startup | resume | clear, SessionStart only) The trigger source.
• reason: (exit | clear | logout | prompt_input_exit | other, SessionEnd only) The reason for session end.
• trigger: (manual | auto, PreCompress only) What triggered the compression event.
• notification_type: (ToolPermission, Notification only) The type of notification being fired.
• message: (string, Notification only) The notification message.
• details: (object, Notification only) Payload-specific details for the notification.

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Output Schema (stdout)

If the hook exits with 0, the CLI attempts to parse stdout as JSON.

Common Output Fields

Field	Type	Description
decision	string	One of: allow, deny, block, ask, approve.
reason	string	Explanation shown to the agent when a decision is deny or block.
systemMessage	string	Message displayed to the user in the CLI terminal.
continue	boolean	If false, immediately terminates the agent loop for this turn.
stopReason	string	Message shown to the user when continue is false.
suppressOutput	boolean	If true, the hook execution is hidden from the CLI transcript.
hookSpecificOutput	object	Container for event-specific data (see below).

hookSpecificOutput Reference

Field	Supported Events	Description
additionalContext	SessionStart, BeforeAgent, AfterTool	Appends text directly to the agent’s context.
llm_request	BeforeModel	A Partial<LLMRequest> to override parameters of the outgoing call.
llm_response	BeforeModel	A full LLMResponse to bypass the model and provide a synthetic result.
llm_response	AfterModel	A Partial<LLMResponse> to modify the model’s response before the agent sees it.
toolConfig	BeforeToolSelection	Object containing mode (AUTO/ANY/NONE) and allowedFunctionNames.

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Stable Model API

Gemini CLI uses a decoupled format for model interactions to ensure hooks remain stable even if the underlying Gemini SDK changes.

LLMRequest Object

Used in BeforeModel and BeforeToolSelection.

💡 Note: In v1, model hooks are primarily text-focused. Non-text parts (like images or function calls) provided in the content array will be simplified to their string representation by the translator.

{
  "model": string,
  "messages": Array<{
    "role": "user" | "model" | "system",
    "content": string | Array<{ "type": string, [key: string]: any }>
  }>,
  "config"?: {
    "temperature"?: number,
    "maxOutputTokens"?: number,
    "topP"?: number,
    "topK"?: number
  },
  "toolConfig"?: {
    "mode"?: "AUTO" | "ANY" | "NONE",
    "allowedFunctionNames"?: string[]
  }
}

LLMResponse Object

Used in AfterModel and as a synthetic response in BeforeModel.

{
  "text"?: string,
  "candidates": Array<{
    "content": {
      "role": "model",
      "parts": string[]
    },
    "finishReason"?: "STOP" | "MAX_TOKENS" | "SAFETY" | "RECITATION" | "OTHER",
    "index"?: number,
    "safetyRatings"?: Array<{
      "category": string,
      "probability": string,
      "blocked"?: boolean
    }>
  }>,
  "usageMetadata"?: {
    "promptTokenCount"?: number,
    "candidatesTokenCount"?: number,
    "totalTokenCount"?: number
  }
}