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

With no annotations, the description carries full weight. It discloses that search is semantic, that only published paths are searched, that nothing is generated on demand, and that unmatched subjects have no path. This gives an accurate model of what the tool does and does not do.

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 longer than average but every paragraph contributes: what learning paths are, when to use this tool vs. alternatives, querying guidance, and behavioral caveats. The structure is logical with a clear opening statement, though the intermediate explanatory paragraph about Vectree could be trimmed without losing essential guidance.

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 two-parameter search tool with no output schema and no annotations, the description fully covers purpose, usage, parameter semantics, and edge cases. An agent has everything needed to call it correctly and interpret the result caveats.

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% for both parameters. The description adds meaningful context beyond the schema by explaining that query should be natural language and that full sentences work better than keywords, which helps the agent construct a better query.

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 opens with a precise verb and resource: 'Search Vectree's curated learning paths' and distinguishes them from individual diagrams. It explicitly names the sibling 'search_diagrams' as the alternative for single topics, so an agent can tell exactly which tool to pick.

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?

Provides an explicit when-to-use rule ('learn, study or get started with a whole subject') and names the alternative with the condition that selects it ('specific topic explained... use search_diagrams'). Also advises on query phrasing, which is directly actionable.

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