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Wafergraph MCP

by com.wafergraph

Rank companies by connectivity

rank_by_connectivity

Rank companies by documented supply-chain degree: customer count (downstream reach), supplier count (upstream dependence), or total. CRITICAL: degree measures how well a relationship is DOCUMENTED in this curated dataset, not how critical the company actually is — a well-covered firm can outrank a more essential but obscure one. See the caveat field in every response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax number of companies to return (1-50, default 15).
metricNo'customers' = downstream reach, 'suppliers' = upstream dependence, 'total' = sum of both.total
countryNoRestrict to companies headquartered in this country (case-insensitive exact match).
segmentNoRestrict to companies in this taxonomy segment id (see get_segments).

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It honestly discloses the ranking is based on documented degree, not actual criticality, and mentions a caveat field in responses. However, it does not discuss other behavioral traits like rate limits or side effects.

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-loading purpose and then a critical caveat. Every sentence adds value, no wasted words.

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 there is no output schema, the description mentions a caveat field in every response, hinting at return structure. It covers the core ranking behavior and constraints, though it could briefly describe the output format (e.g., list of companies with scores).

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 schema already describes parameters. The description adds value by explaining the meaning of the metrics (customer count, supplier count) and the documentation caveat, which goes beyond schema descriptions.

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 clearly states the tool ranks companies by documented supply-chain degree using customer count, supplier count, or total. It uses specific verbs ('rank') and resources ('companies by connectivity'), and the caveat distinguishes its focus from other ranking tools like rank_by_market_cap.

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 provides a critical caveat about documentation versus actual criticality, guiding appropriate use. It does not explicitly state when not to use or suggest alternatives, but the sibling tool list implies this is for connectivity-focused ranking.

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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