zurich_datastore_sql

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

Annotations already indicate read-only and non-destructive behavior. The description adds that only SELECT queries are allowed and returns JSON results, which aligns with annotations and provides useful behavioral context beyond what annotations offer.

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

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

The description is concise with three sentences, front-loads the purpose, and avoids unnecessary details. Every sentence adds value.

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

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

Given the tool's complexity (SQL queries) and the presence of an output schema (context indicates it exists), the description covers input, constraints, and output format. It could mention error handling or performance but is adequate for agent selection.

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

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

The input schema already includes a description with an example. The tool description adds constraints (only SELECT) and capability (complex queries) that are not in the schema, providing some added value, but does not elaborate on parameter format or validation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it executes SQL queries on the CKAN DataStore, specifying it supports complex queries like JOINs and GROUP BY, and only SELECT is allowed. This differentiates it from sibling tools like zurich_datastore_query.

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

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

The description does not provide explicit guidance on when to use this tool versus alternatives such as zurich_datastore_query. It only implicitly suggests it's for complex SQL queries but lacks when-not-to-use or alternative comparisons.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.