jules_create_task

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

With no annotations, the description carries the full burden. It usefully discloses the workflow Jules performs (checkout, inspect files, formulate a plan, prepare a PR), which is real behavioral context beyond the schema. However it omits that the operation is asynchronous, what identifier is returned, whether it requires GitHub authorization, and that a PR is only "prepared" rather than merged or that a plan-approval gate (per autoApprovePlan) is involved.

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

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

Two sentences, zero waste, and the core action is front-loaded ahead of the workflow detail. Every clause earns its place by telling the agent what happens after invocation.

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

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

For a 6-parameter creation tool with no annotations and no output schema, the description covers the purpose and downstream workflow but says nothing about the return value (a task ID the agent will need for jules_get_task_status/jules_approve_plan) or the async nature of the call. It is adequate but leaves an operational gap an agent must discover empirically.

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

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

Schema description coverage is 100%, and the six parameters are documented with examples and defaults (owner/repo format, baseBranch default "main", autoApprovePlan default false). The description adds no parameter-level detail beyond the schema, so the baseline of 3 applies.

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

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

States a clear verb+resource ("Creates a new autonomous coding task") and a specific target system (Google Jules AI), which cleanly separates it from the read/manage siblings (list, get_status, approve_plan, cancel). It does not explicitly name an alternative tool or clarify its relationship to jules_approve_plan, so it stops short of full sibling differentiation.

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

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

No when-to-use, when-not-to-use, or alternative guidance is given. The agent must infer that this is the initiating tool in the lifecycle, and there is no mention of prerequisites (e.g., a connected GitHub account or that a task must exist before jules_get_task_status or jules_approve_plan apply).

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