load_rdf_file

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

With no annotations, the description carries the behavioral burden and does real work: format auto-detection from extension, the rule that quad formats override any target graph, and the token-cost rationale for the file path. It omits mutation semantics of mode=replace (does it drop existing triples?) and any auth or async/task behavior, which are meaningful for a data-loading write.

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?

Three short paragraphs, front-loaded with the action and followed by format rules and rationale. The token-cost sentence is a concise justification for the tool's existence rather than filler; nothing is wasted.

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 tool with no annotations and no output schema, the description covers formats, mode, and graph interaction well. The remaining gap is the return/execution model (synchronous vs. a task tracked via task_status) and the exact effect of replace mode, which the agent cannot infer from structured fields.

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?

Schema coverage is 100%, so the baseline is 3, but the description genuinely adds meaning beyond the schema: it explains that media type is inferred from the file extension and that the graph parameter must be omitted for quad formats because the file defines graph names. That interaction is not derivable from the parameter descriptions alone.

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?

States a specific verb (Load), resource (RDF file), source (from the sandbox) and destination (into a dataset). An agent can distinguish it from write_graph and sparql_update, which serve inline or in-conversation writes, without opening any schema.

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?

Gives clear context for using this over passing RDF inline (contrasted with INSERT DATA) and an explicit exclusion: 'do not pass a target graph' with TriG/N-Quads. It stops short of naming the sibling tools (sparql_update, write_graph) that would be the alternatives, so this is strong context rather than full routing.

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