Export Research Dataset

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

Annotations already declare readOnlyHint and idempotentHint true, so the description does not need to restate non-destructiveness. It adds value by specifying the output format (JSON-serialisable dicts) and providing example usage, which clarifies the behavior beyond 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 well-structured with a clear purpose, usage scenarios, and a concrete example. It is not overly verbose, though the example could be slightly shortened without losing utility.

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 output schema exists, the description adequately covers the tool's purpose, output format, and typical use cases. It lacks explanation for the 'limit_per_table' parameter, but the schema provides defaults and constraints. Overall, complete for an export tool.

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 includes descriptions for 'tables' and default/min/max for 'limit_per_table', so schema coverage is effectively not 0%. The description mentions 'tables' in the example but does not explain all options or additive meaning beyond the schema. Baseline 3 is appropriate.

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 exports stored knowledge-graph data for downstream analysis, using specific verbs and identifying the resource. While it distinguishes itself from sibling analysis tools by being an export function, it does not explicitly contrast with siblings like get_knowledge_graph_stats.

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 implies usage for downstream analysis (e.g., pandas, ML) and provides an example, but it does not explicitly state when to use this tool versus alternatives or when not to use it. No exclusions or prerequisites are mentioned.

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