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aalises

Catalunya Open Data MCP

by aalises

bcn.plan_query

bcn_plan_query

Translate natural language questions about Barcelona into structured data queries on Open Data BCN. Get recommended resources, place resolution, and workflow steps without executing the query.

Instructions

Plan a natural-language Barcelona city question into an explainable Open Data BCN workflow. Returns recommended resources, optional source-bounded place resolution, final tool arguments, and citation guidance without running the final data query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNo
sortNo
taskNo
limitNoRows to return. Server maximum: 100.
queryYes
fieldsNo
offsetNo
filtersNo
group_byNo
radius_mNo
place_kindNo
place_queryNo
resource_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
errorNo
provenanceYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It clearly states the tool returns a plan without side effects, listing key output components. It lacks details on authorization or rate limits, which is acceptable for a planning tool.

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 single-sentence description is concise and front-loads the purpose. While it could be more structured with bullet points, it avoids unnecessary words.

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

Completeness3/5

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

The description mentions key outputs and has an output schema, but given the complexity (13 parameters, nested objects), it omits details about the output structure and parameter use, leaving the agent with incomplete context.

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 only 8%, and the description does not explain any of the 13 parameters beyond implying 'query' is the natural-language input. This is a significant gap given the number of parameters.

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 clearly states the tool's function: planning a natural-language Barcelona city question into an explainable workflow, with a list of return items. It distinguishes from sibling tools like bcn_execute_city_query by noting it does not run the final query, but lacks explicit differentiation from bcn_recommend_resources or bcn_resolve_place.

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 explicitly notes the tool is for planning and 'without running the final data query,' guiding when to use it versus execution tools. However, it does not provide exclusions or mention alternatives like bcn_query_resource for direct queries.

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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