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approve_plan

Approve a proposed coding session plan to allow the AI assistant to proceed with implementation when a session awaits approval.

Instructions

Approve Jules's plan for a session.

Use this when a session is in AWAITING_PLAN_APPROVAL state and you want Jules to proceed with its proposed plan.

Args: session_name: Resource name of the session (e.g., "sessions/abc123")

Returns: Success confirmation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It mentions the state transition (AWAITING_PLAN_APPROVAL) and the action (approve), implying a mutation, but lacks details on permissions, side effects, or error handling. It adds some context but doesn't fully cover behavioral traits like what happens on failure or if approval is reversible.

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

Conciseness5/5

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

Well-structured and front-loaded with the purpose, followed by usage guidelines and parameter details. Every sentence adds value without redundancy, making it efficient and easy to parse.

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

Completeness4/5

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

Given the tool has an output schema (returns success confirmation), the description doesn't need to explain return values. It covers purpose, usage, and parameter semantics adequately for a mutation tool, but lacks details on behavioral aspects like error cases or prerequisites beyond state, leaving minor gaps.

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

Parameters4/5

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

Schema description coverage is 0%, but the description compensates by explaining the single parameter: 'session_name: Resource name of the session (e.g., "sessions/abc123")'. This adds meaning beyond the bare schema, clarifying the format and purpose, though it doesn't detail constraints like length or validation rules.

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 clearly states the specific action ('Approve Jules's plan for a session') and the resource ('session'), distinguishing it from sibling tools like create_session or get_session. It precisely defines what the tool does without being vague or tautological.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool: 'when a session is in AWAITING_PLAN_APPROVAL state and you want Jules to proceed with its proposed plan.' This provides clear context and distinguishes it from alternatives like send_message or list_sessions, which serve different purposes.

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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