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get_graph

Return the community/knowledge graph manifest for visualisation.

Useful when the calling agent wants the high-level structure of the key's workspace (clusters, hub nodes, cross-references) rather than the contents of any one page. Returns {nodes, edges, communities, stats} — exact shape mirrors the /api/wiki/graph REST endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral burden. It clarifies that the tool is read-only in nature ('Return', 'for visualisation') and discloses the exact return shape ({nodes, edges, communities, stats}) plus its correspondence to the REST endpoint. For a zero-parameter retrieval tool, this is sufficient behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences with no filler: it states the action, gives the use case, and specifies the return shape. Each sentence adds necessary information, and the most important distinguishing detail is front-loaded.

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?

Given that the tool takes no parameters and an output schema is reportedly available, the description covers everything an agent needs: what the tool does, when to use it, and what shape the result takes. There are no hidden inputs or ambiguous prerequisites.

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 the schema coverage is trivially 100%, so there is no parameter meaning for the description to add. The baseline of 4 applies because the description instead clarifies what the returned graph represents, which is the relevant semantic context for this tool.

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 names a specific verb ('Return') and a clear resource ('community/knowledge graph manifest'), and it explicitly contrasts the graph-level view with 'the contents of any one page,' which distinguishes it from siblings like get_page and list_pages. The scope and purpose are immediately identifiable.

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?

The description states when to use the tool: when the agent wants the high-level workspace structure rather than page contents. It does not explicitly name alternative tools or list exclusions, but the 'rather than' phrasing gives enough contextual guidance for an agent to select this tool appropriately.

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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