compare_companiesSide-by-side comparison of 2-6 companies on the same fields, plus their shared and unique supply-chain counterparties. Cheaper and more aligned than several get_company calls when the question is comparative.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | Yes | Company ids (snake_case, e.g. ['tsmc','samsung_foundry']) or exact names. 2-6 of them. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full weight. It explains the tool compares companies on 'same fields' and supply-chain counterparties, but lacks details on data freshness, authorization requirements, pagination, or what 'same fields' entails. Adequate for basic understanding but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero wasted words. The first sentence states core functionality, the second provides comparative advantage. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 1 parameter and no output schema, the description covers purpose and usage well. However, it omits detail on what output the agent should expect (e.g., fields compared, format). Lacks completeness on output expectation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (single 'ids' parameter already described in schema). The description only reiterates '2-6 companies' without adding new meaning, such as accepted formats or constraints beyond what the schema already states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies a concrete verb ('compare'), resource ('companies'), and scope ('2-6 companies on the same fields, plus shared/unique supply-chain counterparties'). It clearly distinguishes this tool from siblings like 'get_company' (single company) or 'analyze_portfolio_exposure'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool over alternatives: 'Cheaper and more aligned than several get_company calls when the question is comparative.' This provides clear context for appropriate usage, though it could mention situations where this tool is not suitable (e.g., deep dives on individual companies).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.