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Skeego

opendata-mcp

by Skeego

get_community_datasets_v1_graph_communities__community_id__datas

Retrieve datasets within a specific graph community, sorted by importance, to discover key open data resources.

Instructions

GET /v1/graph/communities/{community_id}/datasets (public) — Get Community Datasets — List datasets in a graph community, ordered by importance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
community_idYes
limitNo
offsetNo
Behavior3/5

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

The description adds a 'public' tag, hinting at open access, and states ordering by importance. However, no annotations are provided, leaving the tool's safety profile unconfirmed. It doesn't mention that this is a read-only operation (though GET implies it), nor does it disclose behavior like pagination, rate limits, or what happens if community_id is invalid. Some behavioral context is given, but not enough to fully compensate for missing annotations.

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 concise in one sentence but includes some redundancy (the HTTP method and 'public' tag are arguably unnecessary for an AI agent). It front-loads the key operation. Minor improvement could remove the HTTP prefix.

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 no output schema and no annotations, the description should cover return format, pagination, and authentication. It only mentions ordering and public access. Without output schema, the agent knows little about the response. This is incomplete for a tool that is likely used in data retrieval workflows.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must explain parameters. The description only mentions community_id implicitly via the URL path but does not describe limit or offset parameters. It fails to add meaning beyond the schema structure. For a tool with 3 parameters and no schema descriptions, this is insufficient.

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?

Description explicitly states 'List datasets in a graph community, ordered by importance.' It uses a specific verb (list) and resource (datasets in a community), with ordering detail. This clearly distinguishes it from sibling tools like get_communities (which lists communities) or get_related_datasets (which lists related datasets for a given dataset).

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

Usage Guidelines3/5

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

Description implies usage when needing datasets in a community, but provides no guidance on when not to use it or how it compares to alternatives like get_related_datasets or get_entity_datasets. No exclusions or prerequisites are mentioned. With many sibling tools, this is a moderate gap.

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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