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process_auth_code_tool

Process OAuth2 authorization codes for Gmail integration by validating Google-provided code and state parameters to authenticate access.

Instructions

    Process the OAuth2 authorization code and state.
    
    Args:
        code (str): The authorization code from Google.
        state (str): The state parameter from Google.
        
    Returns:
        str: A success or error message.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
stateYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions processing OAuth2 codes and states but lacks critical details: it doesn't specify if this completes authentication, stores tokens, requires specific permissions, or handles errors beyond returning a message. For a security-sensitive OAuth tool with zero annotation coverage, this is a significant gap in transparency.

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?

The description is well-structured and front-loaded with the core purpose, followed by clear Arg/Return sections. Every sentence adds value: the first defines the tool's role, and the subsequent lines document parameters and output without redundancy. It's appropriately sized for a simple tool with two parameters.

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

Completeness3/5

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

Given the tool's complexity (OAuth processing, 2 parameters, no annotations, no output schema), the description is minimally adequate. It covers the basic purpose and parameters but lacks details on behavioral outcomes, error handling, and integration with sibling tools. Without annotations or output schema, it should do more to guide safe and correct usage in an authentication context.

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%, so the description must compensate. It adds meaningful context by explaining that 'code' and 'state' come from Google OAuth, which clarifies their origin and purpose beyond the bare schema. However, it doesn't detail format constraints (e.g., code length, state matching), leaving some ambiguity. With 2 parameters and no schema descriptions, this is above baseline but not fully comprehensive.

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

Purpose4/5

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

The description clearly states the action ('Process') and the resources ('OAuth2 authorization code and state'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling authentication tools like 'authenticate' or 'login_tool', which likely handle related OAuth flows, leaving some ambiguity about when to choose this specific tool.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., after receiving a callback from Google OAuth), exclusions, or how it relates to sibling tools like 'authenticate' or 'check_auth_status', leaving the agent to infer usage context from the tool name alone.

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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