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getSchemaMarkdown

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Fetch the full graph schema as compact Markdown before building any query. Returns labels, property types and ranges, relationships, and semantic-search indexes to ensure exact, correct queries.

Instructions

STEP 0 — call this ONCE at the start of every conversation before constructing any query. Returns the complete graph schema as compact Markdown: all labels with record counts, all properties per label with their type and value ranges (min/max for numbers/datetimes, sample values for strings/booleans; array properties render as type[]), and all cross-label relationships with direction and edge property summaries. The Properties table includes a "Semantic Search" column: properties with an embedding index show sourceType similarityFunction dimensionsd [status] (e.g. managed cosine 1536d [ready]); others show —. A non-— value means the property is queryable with aiSemanticSearch. This single call replaces the need for separate findLabels + findProperties + findRelationships discovery calls. Use the result to determine exact label names (case-sensitive), field names, field types, and relationship patterns before building any findRecords query. Optionally pass labels array to narrow the output to specific labels. Pass force: true to bypass the 1-hour schema cache and force a fresh recalculation.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`force`	No	Pass true to bypass the 1-hour schema cache and force a fresh recalculation.
`labels`	No	Optional: scope schema to specific labels only. Leave empty to get all labels.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`markdown`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.0.1Oct 21, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint/non-destructive), and the description adds genuinely new behavior: the 1-hour schema cache and how force bypasses it, plus the semantics of the Semantic Search column. This is strong added context; the only minor gap is not stating output size/truncation behavior for very large schemas.

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 imperative 'STEP 0 — call this ONCE...' is front-loaded and the dense middle enumerates exactly what the return contains. It is long, but nearly every clause carries information (cache, semantic column, replacement of three calls); minor trimming of the output-format detail would tighten it.

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 discovery tool returning a large structured payload, the description explains scope, invocation timing, caching, and how to interpret the Semantic Search column, and it routes the agent to the follow-up (findRecords). Nothing needed to call it correctly is missing.

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 coverage is 100%, so both parameters (force, labels) are already fully documented in the schema, and the description's statements about them largely restate that. 'Leave empty to get all labels' adds a small clarification, but this is the baseline case where the schema does the heavy lifting.

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: returns the complete graph schema as compact Markdown, enumerating exactly what is included (labels with counts, properties with types/ranges, relationships with direction). It explicitly differentiates from sibling discovery tools by declaring it replaces findLabels + findProperties + findRelationships.

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?

Explicit 'STEP 0 — call this ONCE at the start of every conversation before constructing any query' gives unambiguous when-to-use. It also names the alternative discovery calls it supersedes and states the sequencing relative to findRecords, leaving nothing to inference.

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