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corporate_lobbying_by_ticker

Retrieve normalized corporate lobbying filings for a stock ticker, including income, expenses, issue codes, and government entities, with optional date filtering and JSON or CSV output.

Instructions

Normalized corporate lobbying filings: { format: "json", ticker, name, series: [{date, filing_uuid, filing_year, quarter, client_name, registrant_name, income, expenses, issue_codes, government_entities, cik}, ...], series_count, series_total } CSV returns the sliced series.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reqYes
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only shows the output JSON structure and mentions that CSV returns the sliced series. It does not mention read-only nature, rate limits, pagination, or any side effects. This is minimal behavioral transparency for a data retrieval tool.

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 concise, using a compact JSON sample to convey the output format and a single line about CSV behavior. It avoids fluff and is front-loaded with the core concept. The structure is clear and efficient.

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?

For a tool with nested objects and no annotations or output schema, the description should provide more context. It shows the output structure but omits error handling, filtering semantics, and the overall purpose. The schema has parameters that are not elaborated, making it incomplete for an agent to fully understand when and how to use it.

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

Parameters1/5

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

Schema description coverage is 0% (the schema itself only describes date formats). The description does not explain the parameters (limit, format, date_from, date_to) or how they affect the output. The output structure is shown but not linked to parameters. No added value over the schema.

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

Purpose3/5

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

The description starts with 'Normalized corporate lobbying filings:' which implies the resource but does not explicitly state the action (e.g., 'retrieves', 'returns'). The name 'corporate_lobbying_by_ticker' is self-explanatory, but the description does not differentiate from other *_by_ticker tools. It provides the output structure but not a clear purpose statement.

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. There are many sibling tools with similar patterns, but no mention of criteria for selection, such as 'use this to get lobbying data for a specific ticker' or exclusions. The agent is left to infer usage from the 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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