aeroedu_kg_search

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

Annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true) are consistent. The description adds that the AI analyzes the query semantically and returns specific node information, but does not mention rate limits or error handling. Overall, it provides reasonable behavioral context 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 concise (3-4 sentences) and front-loaded with purpose. It includes examples but could be more structured (e.g., separating purpose, usage, output). Still, it is efficient and clear.

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 schema coverage and annotations, the description explains the return format and typical usage. It does not cover pagination, sorting, or edge cases, but for a search tool with high schema coverage, it is fairly complete.

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 each parameter has a description. The description adds example queries but no additional detail per parameter beyond what the schema provides. 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 performs semantic search in AeroEdu's Knowledge Graph using natural language, specifying it returns nodes with descriptions, subject, grade, difficulty, and links. It provides examples and distinguishes itself from sibling tools like node_detail and path_find.

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 gives examples but does not explicitly state when to use this tool versus alternatives (e.g., node_detail for specific nodes, path_find for paths). While siblings provide context, the description lacks direct usage guidance.

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