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government_contracts_by_ticker

Retrieve U.S. government contract awards for a company ticker, including award amounts, agencies, and dates. Filter by date range and output JSON or CSV for analysis.

Instructions

U.S. government contract awards for a single ticker: { format: "json", ticker, name, series: [{award_id, award_amount, award_type, awarding_agency, awarding_sub_agency, recipient_name, start_date, end_date, description, naics_code, naics_description, contract_award_type, cik}, ...], series_count, series_total } CSV returns the sliced series.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reqYes
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the return structure in detail, including the JSON fields and the CSV behavior ('CSV returns the sliced `series`'), which is valuable. However, it does not disclose error behavior, rate limits, or how pagination and date filtering behave beyond what the schema implies.

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 front-loads the purpose in a single line, then provides a structured JSON output example. Although the JSON block is lengthy, it is directly informative for understanding the response shape. No redundant prose is present; it is efficient for what it conveys.

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?

For a simple single-ticker data tool with five nested parameters and no output schema, the description provides a detailed return structure, which is helpful. However, it omits parameter usage and any when-to-use context, making it moderately complete but not fully self-sufficient for an agent deciding how to invoke it.

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%, so the description should compensate but does not. It never explains the parameters (ticker, limit, format, date_from, date_to) except incidentally showing 'format' in the output spec, which could be confused with a parameter. The schema provides some basics (e.g., date format, limits), but the description adds no semantic value.

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 'U.S. government contract awards for a single ticker', which identifies the tool's purpose and distinguishes it from the sibling screener_government_contracts (which is likely for multiple tickers). However, it lacks an explicit verb like 'get' or 'retrieve', making it a noun phrase rather than an action-oriented 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?

There is no guidance on when to use this tool versus alternatives. Although the phrase 'for a single ticker' implies a use case, the description does not mention the sibling 'screener_government_contracts' or explain when to choose one over the other. This leaves the agent to infer context.

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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