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relationships

Graph lane: labelled relationship EDGES between companies/entities (ownership, operates, supplies, …) — the PRODUCT (edges with tiers + provenance), named for the capability, not the meter. Typed query params (GET /relationships): entity (the START NODE — matched as a case-insensitive SUBSTRING of an entity/company NAME, never an id: "3" matches any name containing "3" and resolves to an arbitrary one, so pass a full, distinctive name), hops (traversal DEPTH 1-10, default 1 — the BILLING UNIT: metered per hop, which is why billing_quote takes hops=), relation_type (one relation label — checked against the API's allow-list; unknown -> backend 400), search (free-text), limit (<=100, default 50), offset. Metered — debited from the CALLING agent's own wallet, not the owner's (read it with the joules_balance tool). For the exact per-caller price before you call, use the billing_quote tool (free, tier-aware; returns joules_all_in) or check affordability with the joules_deficit tool; the true debit is the base joule_cost plus a 0.5% rail surcharge rounded up (a 100 J call debits 101 J) = joules_all_in. Preserves source_tier/tier_label on each edge — do not strip them. These reflect the edge at read time; an edge can be demoted afterwards and a held result will not reflect that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hopsNo
limitNo
entityNo
offsetNo
searchNo
relation_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

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 carries the full burden excellently: it discloses billing semantics (metered per hop, debited from calling agent's wallet), surcharge details (0.5% rail surcharge, 100 J -> 101 J), tool routing for price/affordability (billing_quote, joules_deficit), and read-time tier provenance caveats (edges can be demoted). This is rich behavioral context beyond schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose and key constraints, then billing details. Dense but every sentence earns its place. Slightly lengthy due to billing tool routing, but necessary for an agent to avoid wallet mistakes.

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?

Given no output schema, no annotations, and 0% schema coverage, the description is complete: it covers purpose, parameters, billing, sibling tool routing, and output provenance. An agent has everything needed to call correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does: entity is a case-insensitive substring of name (not id), hops is traversal depth 1-10 default 1, relation_type is one label checked against allow-list, search is free-text, limit <=100 default 50, offset. All six parameters are semantically enriched beyond the schema titles.

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?

States a specific verb+resource: labelled relationship EDGES between companies/entities (ownership, operates, supplies). Names the capability and explicitly contrasts with the sibling 'hops' (the meter vs the product). An agent can distinguish this tool from siblings without opening schemas.

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?

Provides clear when-to-use context:

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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