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MuYiYong

nebula-mcp

by MuYiYong

nebula_render_result

Read-onlyIdempotent

Render query results as interactive graphs or tables, with evidence-based explanations, charts, and actual GQL.

Instructions

Display a query result: graph entities open as an interactive graph, otherwise open the table. Supply an evidence-based explanation of result meaning, specific observations, insights and limitations, not only counts. Includes charts and actual GQL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
explanationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
explanationYesExplain result meaning and insights with concrete entities, directions, values and comparisons. Distinguish facts from hypotheses and state sampling/missing-data limits. Do not merely repeat row or path counts.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.4

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds rendering behavior (graph vs table, charts, actual GQL) and the mandatory explanation content, but says nothing about input provenance or failure handling. Adds moderate value over the annotations.

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?

Two tight sentences; the display behavior is front-loaded and the explanation mandate follows. Dense but every clause carries information, with no filler.

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?

A rich output schema ($defs for GraphSpec, TableResult, ChartSpec, ExplanationContext) means return values need not be explained, and the description correctly focuses on display behavior and the required explanation. The remaining gap is not tying the tool to nebula_execute_query as the source of 'result'.

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 at the top level is 0%, so the description must carry the load. It does meaningfully characterize the 'explanation' parameter (evidence-based, observations, insights, limitations, not only counts), but adds almost nothing about what the 'result' parameter should contain, leaving half the parameters unexplained outside the nested $defs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Display a query result', plus the rendering branch (graph entities -> interactive graph, otherwise the table). It is clear what the tool does, but it never explicitly differentiates itself from the sibling nebula_render_graph, leaving the agent to infer the boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives content requirements for the explanation ('not only counts') but no explicit when-to-use versus nebula_render_graph or indication that the result must come from nebula_execute_query. Usage is implied by the input shape rather than stated.

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