get_grounding_information

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

No annotations are provided, so the description carries the full burden. It discloses that the tool extracts information (a read operation) and hints at behavioral traits like different modes and turbo mode, but lacks details on permissions, error conditions, or side effects. It doesn't contradict annotations, but for a tool with no annotations, more behavioral context would be beneficial.

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 appropriately sized and front-loaded, starting with the core purpose followed by parameter and return details. Each sentence adds value, with no wasted words. The structure is clear, though the return type explanation could be slightly more concise.

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 moderate complexity, no annotations, and an output schema that documents return types, the description is fairly complete. It covers purpose, parameters, and returns adequately. However, it lacks context on prerequisites (e.g., needing an open mindmap) and doesn't fully explain sibling differentiation, leaving minor gaps.

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 description adds significant meaning beyond the input schema, which has 0% description coverage. It explains the parameters 'mode' and 'turbo_mode' with details on allowed values ('full', 'content', 'text') and effects ('text only'), and specifies defaults. This compensates well for the schema's lack of descriptions, though it could clarify the exact differences between modes.

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's purpose: 'Extracts grounding information (central topic, selected subtopics) from the mindmap.' It specifies the verb ('extracts'), resource ('grounding information'), and source ('mindmap'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from siblings like 'get_mindmap' or 'get_selection', which might also retrieve mindmap data.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools such as 'get_mindmap' or 'get_selection', nor does it specify prerequisites like requiring an open mindmap. Usage is implied through the action of extraction, but no explicit context or exclusions are provided.

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