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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

list_capabilities

Discover available MCP tools grouped by domain. Start here to find dedicated tools with structured results before using raw SQL, avoiding dialect pitfalls.

Instructions

List all available MCP tools grouped by domain.

Call this tool first to discover what dedicated tools are available before falling back to execute_sql. Dedicated tools return typed, structured results and avoid SQL dialect pitfalls.

Returns: A dict mapping domain name to a sorted list of tool names in that domain. The dict itself is sorted by domain key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 disclosure burden. It discloses the return shape: a dict mapping domain names to sorted lists of tool names, sorted by domain key. The verb 'list' and the discovery framing sufficiently convey that this is a safe, read-only metadata operation.

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 compact and front-loaded with the core purpose. Each subsequent sentence adds distinct value: usage ordering, rationale, and return format. There is no redundant or filler content.

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 zero-parameter discovery tool with an output schema, the description is complete. It explains what the tool does, when to invoke it, why it is preferable to the fallback, and what the returned data structure looks like. No meaningful contextual gap remains.

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 schema coverage is 100%, so there is no parameter semantics to clarify. The description appropriately focuses on return structure rather than input details, which is the only relevant semantic information an agent needs here.

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 uses a specific verb and resource: 'List all available MCP tools grouped by domain.' It clearly distinguishes this discovery tool from the many operational siblings by stating it inventories capabilities rather than performing actions, and it contrasts itself with execute_sql as the dedicated-tool discovery entry point.

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?

The description explicitly instructs the agent to call this tool first before falling back to execute_sql, and explains why: dedicated tools return typed, structured results and avoid SQL dialect pitfalls. This provides clear when-to-use guidance and names the relevant alternative.

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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