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introspect

Discover the registered relation predicates, entity kinds, namespaces, and event types before querying. Call once to learn the graph vocabulary, then verify predicates are actually in use.

Instructions

Return the ontology you navigate by: the registered relation predicates (edge vocabulary, with functional/non-functional semantics), the entity kinds present (node vocabulary with live counts, plus taxonomy metadata — displayName, description, provenance namespace, extends/parent hierarchy, sameAs external URIs — for kinds in the registry), a namespaces summary (core/user/extension: buckets), and the event types recorded. Custom kinds added at runtime appear under the user or extension: provenance namespace. Call once to learn the vocabulary before filtering neighbors/relations/entities. NOTE: this lists what has been registered or extracted, so it can include rarely- or never-populated predicates — e.g. a role/title is usually an attributes.role string on a works_at/founded edge rather than a populated has_role edge — so confirm a predicate is actually in use (via relations) before relying on it. LLM-free.

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description
`views`	Yes	Curated read-only views for the query tool — the stable SQL schema. Query these names, not the physical tables.
`eventTypes`	Yes	Registered event-schema kinds the store records. Empty when no ontology registry is wired.
`namespaces`	Yes	Provenance namespaces aggregated from the registered entity kinds: core (built-in), user (manually added), extension:<name> (plugin-contributed). Predicate provenance joins in a later phase.
`predicates`	Yes	Registered relation predicates — the edge vocabulary for neighbors/relations filtering.
`entityKinds`	Yes	Entity kinds present in the store or registered in the taxonomy, with live counts and optional taxonomy metadata. Includes registered-but-zero-count kinds (e.g. core kinds not yet ingested). Custom kinds added at runtime appear in user or extension namespaces.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 31, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations present, the description carries the behavioral burden and does well: it explains provenance namespace behavior, live counts, taxonomy metadata, and the caveat that registered predicates may be unused. It does not explicitly state permissions or side effects, though 'Return' and 'LLM-free' strongly imply a safe read-only operation.

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?

The description is front-loaded with the core purpose and every clause contributes useful information. The first sentence is long and dense with nested parentheticals, which slightly reduces readability, but it remains efficient for a complex ontology introspection tool.

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?

An output schema exists, so the description need not fully explain return values. Given that, it provides complete context: what is returned, how custom kinds appear, when to call it, and a caution about unused predicates.

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?

The tool has zero parameters and full schema coverage, so parameter semantics are not a concern. The baseline for a parameterless tool is 4.

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 uses a specific verb, 'Return', and a concrete resource, 'the ontology you navigate by', then enumerates relation predicates, entity kinds, namespaces, and event types. It also distinguishes the tool's role by saying to call it before filtering neighbors/relations/entities, making it clearly identifiable among siblings.

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?

It explicitly advises calling once to learn the vocabulary before filtering neighbors/relations/entities, and it points to relations as the way to confirm a predicate is actually in use. It lacks an explicit when-not statement, so it falls short of a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.