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rabidlego25

macro-mcp

by rabidlego25

describe_flow

Get dataflow dimensions, code counts, and a short sample to assess the dataset structure before querying macro statistics.

Instructions

Dimensions of a dataflow with code counts and a short sample.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
flowYes
providerYes
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 reveals what the tool returns (dimensions, code counts, sample) but does not state whether it is read-only, whether it requires special permissions, or what side effects or limitations exist. The word 'describe' weakly implies a safe read operation, but this is not explicit.

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 description is one short sentence with no filler words; it front-loads the core output content. It is concise but perhaps too sparse to fully serve as a standalone definition, though no sentence is wasted.

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?

With two required string parameters, no annotations, no output schema, and no param guidance, the description leaves critical gaps: what counts as a 'flow', how 'provider' should be specified, and what the 'short sample' contains. The description gives a rough idea of the tool's purpose but not enough detail for an agent to call it confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for both required parameters, and the description adds no meaning for 'provider' or 'flow'. It does not explain their format, possible values, or how they identify a dataflow. The description fails to compensate for the lack of schema-level documentation.

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?

The description names the resource ('dataflow') and states the specific output content: dimensions, code counts, and a short sample. Although it is a noun fragment rather than a verb phrase, the tool name 'describe_flow' makes the operation clear. It does not explicitly distinguish itself from siblings like fetch_data or find_dataflows, so it stops short of a 5.

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?

There is no guidance on when to use this tool versus alternatives such as find_dataflows, fetch_data, or search_codes. The description only implies that this tool provides descriptive metadata rather than actual data, but it never states a usage scenario, prerequisites, or exclusions.

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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