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Federal Register Search - US rules, proposed rules, notices

federal_register
Read-onlyIdempotent

Search the official US Federal Register: final rules, proposed rules, notices and presidential documents with abstract, agencies, publication date and links. Filter by keyword, type, agency and date. Free: 25 calls/day per IP. Paid: $0.005 per call via x402 at https://localhost/x402/federal-register.

Input Schema

NameRequiredDescriptionDefault
typeNoRULE, PRORULE, NOTICE or PRESDOCU
orderNonewest or relevancenewest
queryNoKeywords, e.g. artificial intelligence
sinceNoPublished on or after (YYYY-MM-DD)
agencyNoAgency slug, e.g. environmental-protection-agency
maxItemsNoMax results (1-50)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered; the description earns credit for adding quota and cost information the annotations cannot express (25 calls/day per IP free, $0.005 per call via x402). The payment endpoint is given as 'https://localhost/x402/federal-register', which reads as a placeholder and could mislead an agent attempting to use it. Pagination behavior is left to the schema's maxItems.

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?

Three sentences, front-loaded with the capability, then filtering, then cost — each sentence carries information. Minor redundancy in listing document types that the type enum already enumerates, and the pricing sentence is dense with a questionable URL.

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?

For a read-only search tool with no output schema, the description addresses what it does, what comes back, how to narrow, and the cost model. The only meaningful gap is result-set behavior beyond maxItems (pagination/truncation) and the placeholder-looking payment URL, which an agent may need to interpret.

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 already documents all six parameters with enums and defaults. The description restates the filter dimensions but adds nothing the schema lacks, such as valid agency slug discovery or how relevance ordering behaves when no keyword is supplied. Baseline 3 applies.

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 names a specific verb (search) and a specific resource (the official US Federal Register), and enumerates the document classes covered plus the fields returned (abstract, agencies, publication date, links). Sibling tools are unrelated domains (clinical_trials, osv_vulns, prediction_markets), so no cross-routing ambiguity exists to resolve.

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?

It says what can be filtered (keyword, type, agency, date), which implies how to shape a query, but it never states when this tool is the right choice or when it is not. No prerequisites, no exclusions, and no mention of query-construction strategy such as preferring a broad date range when relevance ordering is used.

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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