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ph-civic-data-mcp

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Describe a PSA OpenSTAT dataset

describe_psa_dataset
Read-onlyIdempotent

Retrieve the dimensions and valid value codes for a PSA OpenSTAT dataset, required before querying the dataset.

Instructions

Read the dimensions and valid value codes of one PSA OpenSTAT dataset.

Call this before query_psa_dataset. The query tool needs an explicit value code for every dimension, and those codes live here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_pathYesRelative path to a `.px` dataset, e.g. "1F/FY/0011F3DF010.px". Take it from the `path` field of a browse_psa_catalog dataset entry.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
titleNo
sourceYesUpstream data source name.
caveatsYes
licenseNo
dimensionsYes
source_urlYesCanonical OpenSTAT URL used.
total_cellsNoSize of the full cube.
dataset_pathYes
upstream_errorNoTrue when OpenSTAT was unreachable. Not an empty result.
time_dimensionsNo
validation_errorNoTrue when the caller's arguments were rejected before any request.
data_retrieved_atYes
max_cells_per_queryNo
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds minimal behavioral context beyond the purpose—it notes the codes 'live here' but doesn't describe output details, pagination, or error behavior. It is consistent with annotations but does not significantly enhance transparency beyond them.

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 consists of two concise sentences. The first sentence states the core function, and the second provides essential usage guidance. There is no waste or redundancy, and the most important information 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 the tool's simplicity (one parameter, read-only) and the presence of a detailed input schema and an output schema, the description is complete. It explains the tool's role in the broader workflow, including its relationship with query_psa_dataset and browse_psa_catalog, leaving no critical gaps for an AI agent to resolve.

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 schema description for 'dataset_path' is already highly informative, covering the relative path format, an example, and where to find the value (from the 'path' field of browse_psa_catalog). The tool description does not add any extra parameter meaning. With schema_description_coverage at 100%, the baseline of 3 is appropriate.

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 verb 'Read' and specifies the resource: 'dimensions and valid value codes of one PSA OpenSTAT dataset.' It distinguishes this tool from siblings like query_psa_dataset (which queries data) and browse_psa_catalog (which browses the catalog). This is a specific, unambiguous purpose.

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 says 'Call this before query_psa_dataset' and explains why: 'The query tool needs an explicit value code for every dimension, and those codes live here.' This provides clear when-to-use guidance and references a specific alternative, making the usage context unmistakable.

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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