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cliwant

mcp-sam-gov

by cliwant

regulations_search_comments

Read-only

Search public comments on U.S. federal rulemakings. Filter by agency, docket, date range, and full-text terms to find lobbying data.

Instructions

Search Regulations.gov public COMMENTS on rulemakings — the killer B2G dataset (who is lobbying which rule). Same JSON:API envelope + input shape as regulations_search_documents (searchTerm/query, agencyId, docketId, postedDateGe/Le, sort, pageNumber 1..40, pageSize 5..250) against /v4/comments. Returns { comments:[{ id, documentType, title, agencyId, docketId, postedDate, objectId }] } + honest _meta (same totalElements-exact total + 40-page/10,000-record ceiling handling as documents).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort order (default '-postedDate'). Live-verified set: -postedDate/postedDate/-lastModifiedDate/lastModifiedDate/-commentEndDate (non-exhaustive).
queryNoAlias for `searchTerm` (either is accepted; both feed filter[searchTerm]).
agencyIdNoFilter by posting agency acronym (filter[agencyId]), e.g. 'EPA', 'FDA'.
docketIdNoFilter by docket id (filter[docketId]), e.g. 'EPA-HQ-OAR-2021-0257'.
pageSizeNoRecords per page (page[size]), 5..250, default 25.
pageNumberNo1-based page number, 1..40 (HARD cap — page[number] max is 40; the reachable window is 40×pageSize ≤ 10,000 records).
searchTermNoFull-text search term (filter[searchTerm]), e.g. 'artificial intelligence'.
documentTypeNoFilter by document type (documents only): Rule / Proposed Rule / Notice / Supporting & Related Material / Other.
postedDateGeNoPosted on/after this date, YYYY-MM-DD (filter[postedDate][ge]).
postedDateLeNoPosted on/before this date, YYYY-MM-DD (filter[postedDate][le]).
withinCommentPeriodNotrue ⇒ only documents currently open for comment (documents only; filter[withinCommentPeriod]).
Behavior4/5

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

Annotations already provide readOnlyHint and openWorldHint. The description adds behavioral details such as the same JSON:API envelope, return shape with fields, pagination ceiling (40 pages / 10,000 records), and that totalElements is exact. No contradictions with annotations.

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, front-loaded sentence that efficiently conveys the purpose, input shape, output shape, and important constraints (ceiling, totalElements). Every part adds value without redundancy.

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

Completeness5/5

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

Despite lacking an output schema, the description explicitly lists the return fields and meta structure, including the pagination limit. This is sufficient for an agent to understand what the tool returns and how to use it.

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 baseline is 3. The description adds minimal new info: it notes that 'query' is an alias for 'searchTerm' and mentions the sort set is 'live-verified' and 'non-exhaustive'. However, most parameter details are already in the schema.

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 identifies the tool as searching Regulations.gov public comments, using specific verb 'Search', resource 'COMMENTS', and distinguishes from sibling 'regulations_search_documents' by noting it's the same input shape but for comments. It also states 'killer B2G dataset', providing context.

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

Usage Guidelines4/5

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

The description mentions that the input shape is the same as 'regulations_search_documents', implying a differentiation from that sibling, and notes the endpoint '/v4/comments'. However, it does not explicitly state when to use this tool versus alternatives or when not to use it.

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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