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Hsr Search

hsr_search
Read-onlyIdempotent

Search FTC Hart-Scott-Rodino (HSR) early-termination notices by acquirer or target company name. Matches against the notice title, which embeds both parties and the transaction number, so a partial or one-sided company/fund name finds every notice that mentions it. Use this to check "did this merger get antitrust clearance" or "has the FTC granted HSR early termination for this deal." Example: hsr_search({ party: "Blockbuster", limit: 25 })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax notices to return, newest first. Default 25, max 100.
partyYesCompany or fund name to search for, e.g. "Blockbuster" or "Carl C. Icahn". Matches anywhere in the notice title (as-filed legal name, so include known fund suffixes like "L.P." if a plain name misses).
sinceNoOptional — only return notices on or after this date, YYYY-MM-DD.
_apiKeyNoOptional — your own api.data.gov key for higher limits; omit to use the shared Pipeworx key.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior, so the description correctly adds additional behavioral detail rather than repeating safety traits. It discloses that matching happens against the notice title, that partial or one-sided names will match, and that legal naming conventions like 'L.P.' may matter. This materially helps an agent set expectations.

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 compact, front-loaded with the core action, and every sentence earns its place. The example is illustrative without being redundant, and no filler or restatement of schema fields exists.

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?

For a read-only, single-required-parameter search tool with fully documented parameters, the description provides everything needed to invoke it correctly: a concrete use case, matching semantics, an example call, and expected flexibility of the search term. No output schema is present, but none is necessary for this level of tool complexity.

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 description coverage is 100%, so the baseline is 3. The description adds value beyond the schema by clarifying how the party parameter behaves (partial/one-sided matching against embedded title fields) and by providing a concrete example with the party and limit parameters.

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 opens with a precise verb and resource: 'Search FTC Hart-Scott-Rodino (HSR) early-termination notices by acquirer or target company name.' It clearly establishes the search scope and differentiates itself from siblings like hsr_recent or hsr_party_history by focusing on name-based search across notice titles.

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 gives explicit user-facing scenarios via 'Use this to check...' questions, making the intended use clear. It does not explicitly name competing sibling tools or state when not to use them, but the context is strong enough for an agent to infer appropriate usage.

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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