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jim-coyne

Hyperfabric MCP Server

fabricsGetAllFabrics

Retrieve a list of fabrics from Hyperfabric infrastructure with options to filter by ID, include metadata, and manage pagination for network management.

Instructions

Get the list of fabrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fabricIdNoFilter by one or more fabric ids and or names.
candidateNoThe candidate configuration name. If not set the default candidate configuration values are returned.
includeMetadataNoInclude object metadata in the response.
maxNoThe max number of fabrics to return in the response.
cursorNoThe unique identifier of the cursor representing the position of the next set in the list of fabrics.
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('Get the list of fabrics') without mentioning any behavioral traits such as pagination (implied by 'cursor' and 'max' parameters), read-only nature, authentication requirements, rate limits, or error handling. This lack of context makes it inadequate for a tool with multiple parameters and no output schema.

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 extremely concise with a single sentence ('Get the list of fabrics.'), which is front-loaded and wastes no words. It efficiently communicates the core purpose without unnecessary elaboration, earning a top score for brevity and clarity in structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no annotations, no output schema), the description is incomplete. It fails to explain key aspects like the tool's behavior (e.g., pagination via 'cursor', filtering options), return values, or how it differs from siblings. With no output schema and minimal description, the agent lacks sufficient context to use the tool effectively beyond basic inference.

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?

The input schema has 100% description coverage, providing clear documentation for all 5 parameters (e.g., 'fabricId' for filtering, 'cursor' for pagination). The description adds no additional meaning beyond the schema, as it does not mention parameters at all. According to the rules, with high schema coverage (>80%), the baseline is 3, which is appropriate here since the schema handles the heavy lifting.

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

Purpose3/5

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

The description 'Get the list of fabrics' clearly states the verb ('Get') and resource ('fabrics'), making the purpose understandable. However, it lacks specificity about scope (e.g., all fabrics in a system) and does not distinguish it from sibling tools like 'fabricsGetFabric' (which likely gets a single fabric) or 'fabricsGetFabricConnections' (which focuses on connections). This vagueness prevents a higher score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools (e.g., 'fabricsGetFabric' for a single fabric, 'fabricsGetFabricConnections' for connections), there is no indication of context, prerequisites, or exclusions. This absence of usage instructions leaves the agent to infer based on tool names alone.

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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