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cliwant

mcp-sam-gov

by cliwant

lda_search_filings

Read-only

Search US Senate Lobbying Disclosure Act filings to find who lobbies which federal agency on which issue and how much they are paid. Filter by registrant, client, lobbyist, year, or issue.

Instructions

Search US Senate LDA (Lobbying Disclosure Act) filings — who is paid HOW MUCH to lobby WHICH federal agency on WHICH issue (lda.senate.gov/api/v1/filings, KEYLESS — anonymous access works; an optional free LDA_API_KEY only raises the rate limit). All inputs optional: registrantName (the lobbying firm/in-house filer), clientName (who it's for), lobbyistName, filingYear (4-digit), filingType (short code, e.g. 'Q1'/'RR'/'YE'), agency (NOTE: /filings/ has NO server-side agency filter — the LDA API silently ignores it, so it is reported in _meta.filtersDropped and NOT applied; government entities are nested per activity in lobbyingActivities[].governmentEntities), issue (specific lobbying issues text), page (1-based, default 1), pageSize (1..25, default 25). Returns { filings:[{ filingUuid, filingType, filingYear, filingPeriod, incomeUsd, expensesUsd, registrant, client, lobbyingActivities:[{ issueCode, description, governmentEntities:[names] }], documentUrl, postedDate, terminationDate }] } + honest _meta. HONESTY: totalAvailable is the API's REAL total match count (the corpus is ~1.95M filings) — NOT the rows on this page; pagination is page-based (pass the next page number when hasMore). incomeUsd/expensesUsd are parsed from the null-or-decimal-string income/expenses — null (not reported) ⇒ null, NEVER 0 (a genuine 0 stays 0); a filing reports EITHER income OR expenses, so the other is typically null. Missing lobbying_activities/government_entities ⇒ empty arrays (never fabricated). A genuine no-match (results:[]) ⇒ honest empty (returned:0); a 400 (bad filter) ⇒ invalid_input surfacing the API's message; a 429 ⇒ rate_limited THROWS (Retry-After honored, never routed around); a 5xx/timeout ⇒ upstream_unavailable THROWS; a 200 non-JSON / non-array results / non-number count ⇒ schema_drift. The optional key rides ONLY in the Authorization: Token header (never the URL/_meta).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-based page number (default 1). Page with the next page number from _meta.notes / when _meta.pagination.hasMore.
issueNoFilter by the specific lobbying issues text (maps to filing_specific_lobbying_issues), e.g. 'appropriations'.
agencyNoNOTE: the keyless /filings/ endpoint has NO server-side government-entity filter — the LDA API silently ignores it, so this value is NOT applied (reported in _meta.filtersDropped, never as a narrowed total). Government entities are nested per lobbying activity (each filing's lobbyingActivities[].governmentEntities); to find who lobbied an agency, narrow by registrantName/clientName/issue and inspect those nested entities. Retained for discoverability of the limitation.
pageSizeNoFilings per page, 1..25 (the LDA API caps at 25), default 25.
clientNameNoFilter by the client name (who the lobbying is FOR), e.g. 'Google'. Substring match, upstream-validated.
filingTypeNoFilter by the filing type short code (e.g. 'Q1' Q1 report, 'RR' registration, 'YE' year-end). A bad code ⇒ upstream HTTP 400 ⇒ invalid_input (surfaced).
filingYearNoFilter by filing year, a 4-digit year (e.g. '2024'). Validated ^\d{4}$.
lobbyistNameNoFilter by an individual lobbyist's name. Substring match, upstream-validated.
registrantNameNoFilter by the registrant (the lobbying firm / in-house filer) name, e.g. 'Akin Gump'. Substring match, upstream-validated.
Behavior5/5

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

Annotations mark readOnlyHint=true, and the description adds extensive behavioral details: keyless anonymous access, rate limit handling, honest pagination, specific handling of income/expenses (null vs 0), empty arrays, and error types (400, 429, 5xx, schema_drift). This provides exceptional transparency beyond the annotations.

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 comprehensive and well-structured, starting with purpose, then parameter notes, return format, and error handling. While somewhat lengthy, each sentence adds unique value; no waste. Minor conciseness improvement possible by grouping related notes.

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?

Given no output schema, the description provides a detailed return structure and covers all critical aspects: input parameters, pagination, data interpretation, error states, and authentication. It leaves no significant gaps for a complex API with 9 optional parameters.

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

Parameters4/5

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

Schema coverage is 100%, baseline 3. The description adds valuable context: agency filter is silently ignored, authentication key goes in header, validation for filingYear, and filingType mapping examples. This enhances the schema definitions without redundancy.

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 it searches US Senate LDA filings and enumerates available filters (registrantName, clientName, etc.). It distinguishes from sibling tools by being specific to lobbying data, with no ambiguity.

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 explains when to use the tool (searching LDA filings) and details all parameters being optional. It notes the agency filter limitation and advises alternative approaches (inspecting lobbyingActivities). However, it does not explicitly state when not to use it or list alternative tools, though siblings are clearly other government data tools.

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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