signals

acquisitions

Read-only

List acquisition and merger events ordered by announcement date, newest first. Filter by payment type, deal amount range, merger flag, or a company that is the acquirer or target. Costs one credit per returned record.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum records to return (1-100). Each returned record costs one credit.
`since`	No	Return records announced on or after this date (YYYY-MM-DD) or ISO-8601 timestamp.
`until`	No	Return records announced on or before this date (YYYY-MM-DD, inclusive) or ISO-8601 timestamp.
`cursor`	No	Opaque pagination cursor returned as pagination.nextCursor on the previous page.
`isMerger`	No	Filter to mergers (true) or acquisitions (false).
`companyId`	No	Return only events where this company is the acquirer or target.
`countries`	No	Headquarters country codes (ISO alpha-2, OR). Pass "unknown" to include companies with no country on file.
`naicsCode`	No	NAICS 2022 code for the target (acquired) company. Matches the code and everything beneath it, so "51" also returns 5132 and 5173. Sector ranges work: "31-33" returns all manufacturing.
`verticals`	No	Target company sector filters (OR). Canonical values: ai, fintech, saas, devtools, healthcare, climate, robotics, cybersecurity, logistics, commerce, data, crypto, media, education, marketing, telecom, realestate, hardware, gaming, space.
`paymentType`	No	Payment type filters. Canonical values: cash, stock, mixed, undisclosed.
`maxAmountUsd`	No	Maximum deal amount in USD.
`minAmountUsd`	No	Minimum deal amount in USD.
`industryGroups`	No	Company industry groups (OR). Matched literally against the LinkedIn labels. Pass "unknown" for companies with no industry on file.

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavior beyond annotations: the credit cost per returned record and the deterministic ordering. This is exactly the kind of operational context an agent needs.

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?

Two sentences with no redundancy: the first states the core operation and ordering, the second lists filtering capabilities and the credit cost. The most important facts are front-loaded, and every sentence earns its place.

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 13-parameter read-only list tool, the description covers the essential operational facts: entity type, ordering, available filters, and cost. With no output schema, it could theoretically list return fields, but the annotations and rich parameter descriptions compensate for most gaps. Pagination is left to the schema's cursor description, which is acceptable.

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 baseline is 3. The description echoes some parameter concepts such as payment type, deal amount range, merger flag, and companyId, but does not add meaning beyond the schema. It omits mention of date filters, countries, NAICS, verticals, and pagination, though the schema fully documents those.

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 specific verb and resource: 'List acquisition and merger events', with ordering specified as 'by announcement date, newest first'. This clearly distinguishes it from sibling tools like funding_events or exec_moves by naming the exact event category covered.

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 clear context for when this tool is appropriate: M&A event lookup against data sources, with a focused set of filters for payment type, deal amount, merger flag, and company involvement. It does not explicitly name alternatives or exclusion criteria, but the event-type framing makes the use case evident.

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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TDQS

A4/5.0

Disambiguation5/5

Each tool targets a clearly distinct resource or action: event types (acquisitions, funding_events, exec_moves), entities (companies, investors), and watchlist operations. The watchlist CRUD commands are separated by function, and company_timeline is clearly scoped to a single company's full history.

Naming Consistency4/5

Watchlist tools consistently use verb_noun (create_watchlist, get_watchlist, add_to_watchlist), while data lookup tools use plural nouns describing the returned entity or event (companies, investors, funding_events). The mixed convention is readable and predictable, with only company_timeline deviating from both patterns.

Tool Count5/5

With 11 tools, the server is well-scoped for its domain: company/event data search plus watchlist management. Each tool has a defined role and the count feels neither sparse nor bloated.

Completeness4/5

The toolset covers the core domain well: company and investor search, major event types, company timelines, and full watchlist membership management. A notable minor gap is the absence of a delete_watchlist tool, since create/list/get/add/remove exist for watchlists.

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