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1franky

Data Platform MCP

by 1franky

generate_report

Turn natural language questions into validated SQL, execute them against a database connection, and export the results as XLSX, PDF, CSV, JSON, or HTML.

Instructions

Generate SQL, execute it under full revalidation and export it inline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatYesFile formats a report can be exported to.
max_rowsNo
questionYes
connection_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatYesFile formats a report can be exported to.
periodNo
messageYes
outcomeYesTerminal outcome of one SQL generation attempt.
payloadNo
is_emptyNo
questionYes
row_countNo
error_codeNo
truncationNo
generated_atYes
clarificationNo
connection_idYes
applied_filtersNo
contract_versionNo1.0.0
Behavior2/5

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

With no annotations, the description must fully disclose behavioral traits. It mentions 'full revalidation' as a safety mechanism but does not explain whether the query is read-only, what permissions are needed, or what side effects execution may have. 'Export inline' is also undefined, leaving significant gaps about the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no filler, efficiently conveying a three-step process. However, it is under-specified for a tool with four parameters and no annotations, which is more under-specification than conciseness. It is concise but at the cost of necessary detail.

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?

The tool has four parameters, no annotations, and low schema coverage. While an output schema exists, the description omits critical details like the meaning of 'full revalidation', how exporting works, parameter roles, and any constraints. This is insufficient for an agent to use the tool 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 only 25% (only format has a description). The description does not mention connection_id, question, max_rows, or format, and adds no semantics beyond the schema. With such low coverage, the agent must guess how to populate these fields correctly.

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 states a clear pipeline: generate SQL, execute it with revalidation, and export inline. This is a specific verb+resource combination, and the revalidation step helps distinguish it from simpler query tools. However, 'export it inline' is somewhat ambiguous and the report aspect is only implied by the tool name.

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?

No guidance is provided on when to use this tool over siblings like generate_and_execute_query or execute_read_query. There are no conditions, exclusions, or alternative tool references, leaving the agent to infer usage from the tool name and description.

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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