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WillHsiaoNYC

NYC Open Data Capital Projects MCP Server

by WillHsiaoNYC

describe_field

Retrieve official field definitions for NYC Open Data capital project datasets, including allowed values, keys, and notes. Filter by field or dataset name for specific data dictionary entries.

Instructions

Official field definitions (the NYC Open Data data dictionary): description, allowed values, primary/foreign key, limitations, notes. Filter by field (column name or display name) and/or dataset (RAW table name or socrata_id); omit both for the full dictionary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldNo
datasetNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the tool returns field definitions with specific attributes, implying a read-only query. However, it lacks details on response format, rate limits, or authentication requirements.

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 two sentences with no redundant words. The first sentence states the purpose and contents, the second explains parameter usage and special behavior (omitting both for full dictionary). Efficient and front-loaded.

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

Completeness4/5

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

Given no output schema, the description should ideally describe the return structure. It lists the contents (description, allowed values, etc.) but does not specify whether the output is an array, object, or key-value pairs. Still, it provides enough context for an agent to understand what to expect.

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

Parameters5/5

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

The schema has 0% description coverage, but the description adds significant meaning: it specifies that 'field' accepts a column name or display name, and 'dataset' accepts a RAW table name or socrata_id. This clarifies the expected values beyond the schema's type definitions.

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 clearly states the tool returns 'Official field definitions' and enumerates what they include (description, allowed values, primary/foreign key, limitations, notes). This distinctly identifies the tool's purpose and differentiates it from sibling tools that deal with budgets, projects, and schedules.

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 explains the two optional parameters and their usage, including the effect of omitting both (full dictionary). While it does not explicitly state when not to use this tool or compare to alternatives, the sibling tools are unrelated, making the use case clear.

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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