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lzinga

US Government Open Data MCP

fr_search_rules

Search proposed rules, final rules, and agency notices in the Federal Register to track regulatory activity by U.S. government agencies.

Instructions

Search for proposed rules, final rules, and agency notices in the Federal Register. Use to track regulatory activity by agencies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordNoSearch keyword, e.g. 'tariff', 'emissions', 'banking'
doc_typeNoRule type
agencyNoAgency slug, e.g. 'environmental-protection-agency', 'securities-and-exchange-commission'
start_dateNoStart date YYYY-MM-DD
end_dateNoEnd date YYYY-MM-DD
per_pageNoResults per page (default: 20)
significantNoOnly show significant/major rules (true/false)
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions searching but does not disclose behavioral traits like pagination (implied by 'per_page' parameter but not described), rate limits, authentication needs, or what the output looks like (no output schema). The description is minimal, lacking crucial operational context for a search tool.

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 two concise sentences with zero waste: the first states the tool's purpose and resource, and the second provides usage context. It is front-loaded and efficiently communicates essential information without redundancy.

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 the complexity of a 7-parameter search tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., result format, error handling) and does not compensate for the absence of structured output information, making it inadequate for full agent understanding.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents all 7 parameters. The description adds no parameter-specific semantics beyond implying keyword-based search and date filtering, which are already covered in the schema. Baseline score of 3 is appropriate as the schema does the heavy lifting.

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 the specific action ('Search for proposed rules, final rules, and agency notices'), the resource ('Federal Register'), and the purpose ('track regulatory activity by agencies'). It distinguishes itself from sibling tools by focusing on Federal Register documents, unlike siblings that cover economic data, health statistics, or other government domains.

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

Usage Guidelines3/5

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

The description implies usage context ('track regulatory activity by agencies') but does not explicitly state when to use this tool versus alternatives, such as other search tools in the sibling list (e.g., 'regulations_search_documents' or 'congress_search_bills'). No exclusions or prerequisites are mentioned, leaving the agent to infer applicability.

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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