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markchiang

gpt-researcher-mcp

by markchiang

get_report

Generate structured research reports from natural language queries. Specify a report type to receive a summarized synthesis of web research findings.

Instructions

Get a research report based on a query and report type

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
report_typeNo
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 for behavioral disclosure. It only says 'get' a report, which implies a read operation, but it does not disclose potential side effects, permission requirements, rate limits, or what the return value contains. The lack of any additional behavioral context makes this inadequate for a tool with zero annotation coverage.

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 a single, concise sentence that directly states the tool's purpose. Every word contributes to the core message, with no fluff or redundancy. It is front-loaded and efficiently sized for its minimal content.

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

Completeness2/5

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

Given there is no output schema and no annotations, the description should explain what constitutes a report, what the return format is, and how the parameters affect the result. It does none of these. The tool is simple (2 parameters), but the description leaves significant gaps in understanding the tool's behavior and expected inputs.

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

Parameters2/5

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

Schema description coverage is 0%, and the input schema only gives parameter names and types. The description adds little beyond restating the parameter names: 'based on a query and report type' provides minimal context but no detail on valid formats, allowed values, dependencies, or defaults. It does not compensate for the missing schema descriptions.

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 tool gets a report, with a specific verb and resource, and mentions the two inputs (query and report type). It does not explicitly differentiate from the only sibling 'add-note', but the difference is obvious: one adds notes, the other gets reports. This is clear enough for a 4 but not a 5 due to lack of explicit sibling distinction.

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 gives no guidance on when to use this tool versus alternatives, no exclusions, and no context about prerequisite conditions or limitations. It simply states what it does, leaving the agent no direction on when it is the appropriate choice over other tools.

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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