run_sparql

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

Beyond the annotations (readOnlyHint, idempotentHint), the description discloses result caps (500 rows), runtime limit (30 seconds), and timeout behavior on unanchored scans. This is valuable behavioral context that annotations do not provide, and it does not contradict the annotations.

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 somewhat lengthy but well-structured: it starts with purpose, then usage guidance, guardrails, and parameter details. Each sentence adds value, though the guardrails paragraph could be slightly more compact without losing important information.

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 existence of an output schema, the description fully addresses purpose, usage rules, parameter requirements, and operational pitfalls (timeouts, caps). No significant gaps remain for a raw query tool of this complexity.

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 schema only defines 'query' as a string, but the description adds critical requirements: 'a complete SPARQL SELECT query, including its own PREFIX lines.' This clarifies what the parameter must contain, though it stops short of providing a full example or specifying SPARQL dialect details.

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 'Run a raw SPARQL SELECT query' and distinguishes this from sibling structured tools by positioning it as an 'advanced escape hatch' for analytical queries they cannot express, such as cross-cube joins and aggregations.

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?

Explicitly instructs to 'Prefer the structured tools' and specifies when this tool is appropriate: analytical queries the guarded tools cannot express (cross-cube joins, aggregations, custom filters). It also provides concrete implementation guidance, such as always anchoring on a known class to avoid timeouts.

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