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unified_search

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Identifier-driven cross-collection fan-out search. Pass one or more entity identifiers — ticker, bioguide_id, company_cik, recipient_uei, company_name, or cusip — and this tool queries every collection where that field is indexed, returning results grouped by source in one envelope. Congressional-trade and annual financial disclosure results come from STOCK Act and Form 278 filings. The same filings are published free as news at https://keyvex.com/disclosures under 5 U.S.C. § 13107(c). Use this for high-level 'tell me everything about X' questions before drilling into specific source tools. Replaces 6-10 sequential tool calls with a single fan-out. Identifier coverage: - ticker → 13 collections (company_profile, insider_trades, institutional_holdings, congressional_trades, planned_insider_sales, initial_ownership_baselines, activist_ownership, material_events, proxy_filings, xbrl_fundamentals, tender_offers, registration_statements, nport_holdings) - bioguide_id → 2 collections (congressional_trades, annual_financial_disclosures). In both, a record's party is the party the member held on the date of the record (a trade's transaction date, a disclosure's filing date); for a date outside the member's terms in office, the party of their nearest term (the last one before that date, or the first one after it). - company_cik → 11 collections (company_profile, insider_trades, planned_insider_sales, initial_ownership_baselines, activist_ownership, material_events, proxy_filings, xbrl_fundamentals, private_placements, registration_statements, nport_filings) - recipient_uei → 1 collection (federal_contracts) - company_name → 5 name-keyed collections (federal_contracts, enforcement_actions, consumer_complaints, product_recalls, fda_approvals) AND auto- resolves to ticker + company_cik via EDGAR's catalog, cascading into every ticker/CIK adapter above. The unlock for 'tell me everything about Wells Fargo' hitting up to 20 collections in one call. (lobbying_filings is excluded from the fan-out — its 51K-record substring scan is too slow for parallel federation; call get_lobbying_filings directly instead.) enforcement_actions here returns ENFORCEMENT only, as get_enforcement_actions does by default; call get_enforcement_actions with category="all" for the agencies' general news too. When a regulator's site refuses KeyVex (CFTC since 2026-10-07), the freshness block says which records are missing. - cusip → 4 collections (institutional_holdings, activist_ownership, nport_holdings, treasury_auctions) Multiple identifiers can be combined to narrow each source's query (e.g., ticker + bioguide_id will filter congressional_trades by both). Name resolution: when only company_name is supplied, the resolved ticker and CIK come from EDGAR's company_tickers_exchange.json (US-listed names only). Foreign-only or private companies won't resolve to a ticker, but name-keyed collections (CFPB, lobbying, etc.) still receive the substring filter directly. Performance note: company_name fan-out includes substring-filtered collections (lobbying_filings 51K+, federal_contracts) which scan a 5K- record window per source. The full cascade can take 10-40s depending on Firestore region. When latency matters more than coverage, pass sources to whitelist only the ticker/CIK-keyed adapters (typically <1s total). Per-source result count is capped via per_source_limit (default 5, max 50). One slow or failing source returns an error block instead of blocking the rest — check sources_queried vs sources_with_results to see what landed. When you need full result counts and richer filters on one specific collection, call that collection's dedicated tool directly afterward.

Input Schema

NameRequiredDescriptionDefault
cusipNo9-character CUSIP security identifier. Fans out to institutional_holdings, activist_ownership, nport_holdings, treasury_auctions.
limitNoAlias for per_source_limit (this is a fan-out, so the cap is per source). Default 5, max 50.
sinceNoISO date (YYYY-MM-DD). Applied to each collection's primary date field.
untilNoISO date (YYYY-MM-DD). Inclusive upper bound.
tickerNoStock symbol. Case-insensitive. Fans out to 13 collections.
sourcesNoOptional whitelist of source names. Default: all collections that index the provided identifier(s).
bioguide_idNoCongressional bioguide ID (e.g. P000197 for Pelosi). Fans out to 2 collections.
company_cikNoSEC CIK number for an issuer (10-digit, leading zeros). Fans out to 8 SEC collections.
company_nameNoIssuer name (e.g., 'Lockheed Martin', 'Wells Fargo'). Resolves to ticker + CIK via EDGAR catalog (if US-listed) AND substring-filters name-keyed collections (federal_contracts, enforcement_actions, consumer_complaints, product_recalls, fda_approvals). For a company's lobbying activity, call get_lobbying_filings directly — it is excluded here for fan-out latency.
recipient_ueiNoUSAspending recipient UEI. Fans out to federal_contracts only.
per_source_limitNoMax records per source. Default 5, max 50.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/non-destructive, and the description goes well beyond them: per-source capping (default 5, max 50), partial-failure semantics ('one slow or failing source returns an error block instead of blocking the rest'), the sources_queried vs sources_with_results contract, 10-40s latency expectations, and a stale-source freshness block. This is unusually rich behavioral disclosure for a read tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose, usage routing, and performance notes are well front-loaded, but the long 'Identifier coverage' bullet list largely restates per-parameter fan-out counts already present in the schema descriptions (ticker → 13, cusip → 4, etc.), and the bioguide_id party-resolution tangent is verbose. Useful content is interleaved with redundant content.

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?

No output schema exists, and the description compensates fully: it explains the envelope (results grouped by source), the partial-failure error block, and the sources_queried/sources_with_results reconciliation, plus the freshness block. For an 11-parameter federated tool with no output contract, an agent has what it needs to interpret results.

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?

With 100% schema coverage the baseline is 3, but the description adds real interaction semantics the schema cannot express: 'multiple identifiers can be combined to narrow each source's query (ticker + bioguide_id filters congressional_trades by both)', the company_name → ticker + CIK auto-resolution path, and the sources whitelist as a latency lever. It exceeds baseline meaningfully.

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 opening sentence names a specific mechanism ('identifier-driven cross-collection fan-out search') and immediately enumerates the exact identifier inputs that drive it. It distinguishes itself sharply from the sibling get_* collection tools by framing itself as the high-level entry point before drilling down. An agent can tell exactly what this does without opening the schema.

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

Usage Guidelines5/5

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

Explicit routing guidance: 'Use this for high-level tell-me-everything questions before drilling into specific source tools,' plus named alternatives for the cases it does not cover (get_lobbying_filings for lobbying, get_enforcement_actions with category="all" for general agency news, the dedicated collection tool for richer filters). It even states the latency tradeoff that selects the `sources` whitelist. Both when-to-use and when-to-use-something-else are covered.

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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