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get_concept_relations

Typed relations for a concept in the OT+NT concept graph: broader/narrower (taxonomy), causes, part_of, symbol_of, fulfills, contrasts — ~430 edges, hand-reviewed against cited evidence (Phase 5/6, weight>=10 only, see DESIGN.md #5). Excludes the much larger 'associated' fallback tier by default (~139,000 mechanical shared-evidence edges, unreviewed) — pass verb='associated' to include it. verb optional: restrict to one verb (broader | narrower | causes | part_of | symbol_of | fulfills | contrasts | associated).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
verbNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does so well: it discloses edge count (~430), that edges are hand-reviewed against cited evidence, the weight>=10 filter, the Phase 5/6 provenance, and that the excluded tier is unreviewed mechanical data. It omits pagination/limit behavior and any auth or rate-limit context, which keeps it short of a 5.

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 purpose, then the default-scope caveat, then the verb enumeration — a sensible order. The DESIGN.md and Phase references add a little internal noise, but nearly every clause carries decision-relevant information.

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?

An output schema exists, so return values need not be described, and the description covers scope, default behavior, and verb semantics thoroughly. The only real gap is the undocumented 'limit' parameter.

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

Parameters3/5

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 a strong job on 'verb' (full enum list plus the default-exclusion semantics of 'associated'), but says nothing about 'limit' and only implicitly covers 'name'. Partial compensation for a low-coverage 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?

States a specific verb+resource: typed relations for a concept in the OT+NT concept graph, and enumerates the relation types returned (broader/narrower, causes, part_of, symbol_of, fulfills, contrasts). An agent can distinguish this from the sibling get_concept (which returns the concept itself) without opening either schema.

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?

Explicitly explains the default scoping decision (excludes the ~139,000 'associated' fallback tier) and the condition that changes it ('pass verb="associated" to include it'). It does not, however, state when to reach for this tool versus get_concept or concepts_in_passage, so sibling routing is left to inference.

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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