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Wafergraph MCP

by com.wafergraph

Filter companies

filter_companies

Structured multi-criteria screen over all 615 companies: exact segment/subsegment/country/market_position/public filters plus a market-cap range, sortable and paginated. Use this instead of search_companies when the question is a precise filter ('leader-position analog companies in Japan under $20B') rather than a free-text match. Unknown segment/subsegment/country values just return zero results rather than erroring — call get_segments or list_subsegments first if you're not sure a value is valid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows to return, 1-100. Default 25.
offsetNoRows to skip, for paging past the first `limit`. Default 0.
publicNotrue = only publicly traded companies, false = only private ones. Omit for both.
countryNoHeadquarters country, exact match, case-insensitive, e.g. 'Japan'.
segmentNoExact taxonomy segment id, e.g. 'foundry' (see get_segments).
sort_byNoSort field. 'market_cap' sorts descending with unpriced companies last; 'name'/'country' sort ascending. Default 'market_cap'.market_cap
has_tickerNotrue = only companies with a public ticker on file, false = only companies without one.
subsegmentNoExact taxonomy subsegment id, e.g. 'litho' (see list_subsegments).
market_positionNoExact market_position: monopoly | leader | major | challenger | niche.
max_market_cap_usd_bNoMaximum market cap in USD billions (inclusive). Only ~72% of companies have a cap on file — see the response note when this is set.
min_market_cap_usd_bNoMinimum market cap in USD billions (inclusive). Only ~72% of companies have a cap on file — see the response note when this is set.

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It discloses important semantics: exact matching, unknown values returning zero results rather than erroring, and the tool being sortable/paginated. It does not mention response format or data coverage caveats (e.g., ~72% market cap availability), which are in the schema but not the description, so it is not fully exhaustive.

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 three sentences, front-loaded with the core function ('Structured multi-criteria screen') and immediately followed by usage guidance and an edge-case note. Every sentence earns its place with no filler or repetition.

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?

Given 11 parameters, no annotations, and no output schema, the description covers the essential usage context: tool scope, filter types, sorting/pagination, and error behavior. It does not describe the response structure, which would be helpful, but the sibling tools and the tool name imply a company list. Overall, it is sufficiently complete for an agent to select and invoke the tool correctly.

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 coverage is 100%, so the baseline is 3. The description adds a useful cross-reference: 'call get_segments or list_subsegments first if you're not sure a value is valid,' which helps agents validate parameter values. It also groups parameters into filter categories (exact filters + market-cap range), providing a mental model beyond the flat schema.

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 'Structured multi-criteria screen over all 615 companies' and enumerates the exact filter dimensions (segment/subsegment/country/market_position/public, market-cap range), making the tool's scope and function explicit. It clearly distinguishes itself from 'search_companies' by contrasting precise filters with free-text matching.

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?

The description provides an explicit directive: 'Use this instead of search_companies when the question is a precise filter...' and gives a concrete example. It also advises calling get_segments or list_subsegments first when unsure about valid values, effectively telling the agent when to use supporting tools.

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.

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