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Create Jules Session

jules_create_session

Create a new session for Jules AI to execute a coding task on your repository. Provide a task prompt and repository source to start the session.

Instructions

Create a new coding session with Jules AI coding agent.

A session represents a unit of work where Jules executes a coding task on your repository.

Args:

  • prompt (string, required): The task description for Jules to execute

  • title (string, optional): Title for the session

  • sourceContext (object, required): Repository context with:

    • source (string): Resource name like 'sources/github-owner-repo'

    • githubRepoContext (object, optional): { startingBranch: string }

  • requirePlanApproval (boolean, optional): If true, plans need approval

  • automationMode (string, optional): 'AUTO_CREATE_PR' to auto-create PRs

  • response_format ('markdown' | 'json'): Output format

Returns: The created session with ID, state, and URL.

Examples:

  • "Add unit tests for auth module" with source "sources/github-myorg-myrepo"

  • Set requirePlanApproval=true to review plans before execution

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoOptional title for the session
promptYesThe task description for Jules to execute
sourceContextYesThe source repository and branch context
automationModeNoAutomation mode: 'AUTO_CREATE_PR' to auto-create PRs when ready
response_formatNoOutput format: 'markdown' for human-readable or 'json' for structured datamarkdown
requirePlanApprovalNoIf true, plans require explicit approval before execution
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate this is a write operation (readOnlyHint=false), and the description adds behavioral context: it creates a new session and returns ID/state/URL. It also explains how requirePlanApproval and automationMode alter execution. This goes beyond the minimal hints, though it doesn't detail failure modes or source validation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with Args, Returns, and Examples sections, making it scannable. It repeats some schema details but not excessively. The purpose sentence is front-loaded. It earns a solid 4, slightly loses a point for redundancy with the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

All six parameters are described, including nested objects, and it explains the return value (ID, state, URL) which is essential given there is no output schema. Examples clarify usage patterns. This is complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the description does not need to compensate for missing schema docs. It largely restates the schema parameter descriptions with minor additions like example source values and format clarification. This meets the baseline but adds little beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Create a new coding session with Jules AI coding agent,' which is a specific verb+resource statement that clearly distinguishes this from sibling tools like get/list/delete. The conceptual sentence about sessions further clarifies the tool's unique role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context about what a session represents and includes examples of typical use. However, it does not explicitly state when not to use it or point to alternatives (e.g., 'for existing sessions, use jules_get_session'), so it falls short of full exclusionary guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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