sparql_construct

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

With no annotations provided, the description must carry the full burden. It discloses the output format (Turtle) and query forms, but does not mention potential performance implications, error behavior, or that CONSTRUCT/DESCRIBE are read-only. This is a minimal but non-misleading disclosure; no contradictions.

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 consists of two concise sentences that front-load the core function and output format, followed by a clear usage directive. Every word earns its place with no redundancy.

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?

For a simple query tool with two parameters and no output schema, the description adequately covers purpose, output, and usage context. It lacks details on edge cases or error handling but is reasonably complete for the tool's 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 input schema already provides 100% coverage for both parameters (query and repository_id), with clear descriptions. The main description adds no extra parameter details beyond what the schema states, so the baseline 3 applies.

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 the tool executes SPARQL CONSTRUCT or DESCRIBE queries and returns Turtle, which precisely identifies its function. It distinguishes from siblings like sparql_select (tabular results) and sparql_ask (boolean) by specifying the output format and query types.

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 explicitly advises using this tool 'for queries that return RDF triples/graphs,' which provides clear selection criteria. It does not name alternatives like sparql_select directly, but the guidance implies the differentiator, making it useful for an AI agent to choose appropriately.

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