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Query the world model

query_world_model
Read-onlyIdempotent

Answer state and structure questions about ONE entity from the knowledge graph: current and past relations, dependencies, recent changes, evidence, contradictions and uncertainty.

Suited to questions like "where does X work now?", "what does X depend
on?" or "what changed for X this week?". Each relation carries
``estado`` (CURRENT | HISTORICAL | UNRESOLVED | UNKNOWN) and
``confianza`` (0-1). UNRESOLVED relations or open contradictions mean
the current state is ambiguous. For topic-based questions across stored
memories use cognitive_query.

Args:
    subject: Entity name, alias or id.
    aspect: What to return:
        "current_state" (default) — current relations; legacy relations
            without a reliable date are listed under ``unknown``.
        "historical_state" — also relations that are no longer true.
        "contradictions" — open and resolved contradictions.
        "evidence" — relations with their evidence and whether each is
            justified.
        "relationships" — all incoming and outgoing relations, excluding
            the structural root link.
        "dependencies" — transitive current dependencies (depends_on,
            part_of, uses).
        "changes" — what started, ended, was learned late or was resolved
            within ``ventana_dias``.
        "uncertainty" — what is not known with confidence, with a reason.
        "all" — all of the above plus recent facts and episodes.
    at: Optional ISO date: answer as NEXUS knew it on that date, hiding
        what was not yet known or not yet true.
    depth: Hops of neighbors to include via current relations (0-2).
    ventana_dias: Window in days for "changes" (1-365, default 30).

Returns data for the chosen aspect; ``truncated: true`` means the
neighbor traversal hit its node limit.

Input Schema

NameRequiredDescriptionDefault
atNo
depthNo
aspectNocurrent_state
subjectYes
ventana_diasNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: the meaning of estado values (UNRESOLVED/UNKNOWN implies ambiguity), the confianza 0-1 scale, and the truncated:true node-limit signal. It stops short of describing output shape for each aspect, but the additions are substantive.

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 purpose and the sibling distinction, then a structured Args block. Long, but nearly every sentence adds information; minor redundancy in the aspect explanations is the only cost.

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?

For a 5-parameter read tool with no output schema, the description covers purpose, alternatives, all parameters, domain vocabulary, and even a return-value caveat (truncated). An agent has everything needed to select and invoke it 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 coverage is 0%, so the description carries the full burden and does so: every aspect enum value is explained individually, and at, depth, and ventana_dias all get semantics and ranges (date as-of behavior, 0-2 hops, 1-365 days, default 30). This fully compensates for the undocumented 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 precise verb+resource+scope: 'Answer state and structure questions about ONE entity from the knowledge graph'. The explicit 'ONE entity' bounds the scope and the sibling cognitive_query is named, so an agent can distinguish this tool without opening any schema.

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?

Gives the when (state/structure questions like 'where does X work now?' or 'what changed for X this week?') and the when-not with a named alternative: 'For topic-based questions across stored memories use cognitive_query.' Nothing 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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