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execute_tool

Sends the HTTP request for an OpenAPI tool, using tool name and arguments. Use after retrieving its schema for API calls with optional auth.

Instructions

Execute an OpenAPI tool via HTTP.

    Sends the actual HTTP request based on the tool's method and path
    from the OpenAPI spec. Use after search_tools() + get_tool_schema()
    to call the API.

    Args:
        tool_name: Exact tool name (as returned by search_tools)
        arguments: JSON string of parameter values (e.g. '{"owner":"me","repo":"test"}')
        base_url: API base URL (e.g. https://api.github.com). Required if not inferrable.
        auth_token: Bearer token for authentication (optional)
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_urlNo
argumentsYes
tool_nameYes
auth_tokenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the transparency burden. It discloses that it sends an HTTP request and mentions the auth_token is a Bearer token, which is useful. However, it does not warn that the operation may be destructive or non-idempotent, nor does it mention error handling, side effects, or the dependence of the HTTP method on the specific tool being executed.

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 front-loaded with a clear one-sentence purpose, followed by usage context and a structured argument list. It is concise enough but slightly longer than necessary; the Arg list is justified given the need to explain parameter semantics.

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 that an output schema exists, the description needn't detail return values. It covers enough for an agent to know when to use the tool, how to sequence it, and what each parameter means. It lacks details about error conditions or authentication caveats, but those are not critical given the output schema and the tool's straightforward role.

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

Parameters5/5

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

Schema coverage is 0%, and the description compensates fully with an 'Args' block explaining each parameter, including expected format ('JSON string'), examples, and defaults (e.g., 'base_url' required if not inferrable). This adds meaning well beyond the bare schema titles.

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 'Execute an OpenAPI tool via HTTP' and 'Sends the actual HTTP request based on the tool's method and path from the OpenAPI spec,' specifying the exact verb, resource, and mechanism. It distinguishes from siblings like search_tools and get_tool_schema by positioning this as the actual API-calling step.

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 explicitly instructs 'Use after search_tools() + get_tool_schema() to call the API,' giving a clear usage sequence. While it does not enumerate alternatives nor explicitly say when not to use, the context of sibling tools and the provided sequence sufficiently imply the appropriate conditions.

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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