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Find deals by company

find_deals_by_company

Every M&A deal a company took part in, split by role (as acquirer, as target, or other). Matches by dataset id first, then falls back to case-insensitive name matching — necessary because a deal's target is frequently not itself a company in this dataset and carries a null id (e.g. AMD's acquisition of Xilinx lists acquirer id 'amd' but target id null, name 'Xilinx'). Each matched deal carries a match_method ('id' or 'name') so weaker name-only matches are visible to the caller.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesCompany id, exact name, or ticker to search for across all deal parties, e.g. 'amd', 'Xilinx', 'AMD'.

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description fully discloses the matching behavior (id first, then case-insensitive name), the role split, and the match_method field. It also explains the data nuance about null target IDs, providing complete transparency.

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?

Three clear sentences: what the tool does, how it matches, and what it returns. No unnecessary words, well-structured.

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 single-parameter tool with no output schema, the description fully explains the return structure (deals grouped by role, with match_method) and the rationale behind the matching logic, making it complete.

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 covers the one parameter well. Description adds significant value by explaining the matching fallback, role split, and match_method, which goes beyond the schema's description of the input.

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?

Description clearly states the tool returns every M&A deal a company participated in, split by role (acquirer, target, other). This distinguishes it from sibling tools like get_deals which likely returns all deals.

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?

Describes the matching logic and when fallback to name matching is necessary. Could be more explicit about when to use this vs. alternatives like get_deals or get_deal, but the context is clear enough.

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

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: analyzing portfolio exposure, comparing companies, finding chokepoints, getting company details, country exposure, deals, segments, supply chain walk, and company search. No overlap in functionality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case (e.g., 'get_company', 'search_companies', 'find_chokepoints'). The convention is uniform and predictable.

Tool Count5/5

9 tools is well-scoped for a specialized supply chain analysis server. Each tool serves a distinct query or analysis need without being too few or too many.

Completeness4/5

The tool set covers core operations: search, detail, comparison, portfolio analysis, chokepoint identification, country exposure, deals, and supply chain graph traversal. Minor gaps like historical trends or alerts exist but do not hinder primary use cases.