Find Conceptually Similar AI Tools

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

Annotations already declare readOnly, idempotent, non-destructive, openWorld, so safety is covered. The description adds real behavioral context beyond that: the similarity is computed from MiniLM embeddings of name and tagline rather than shared category, telling the agent why results may differ from taxonomy-based tools. It stops short of describing ranking/scoring or result ordering, so not a 5.

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 sentences, front-loaded with the core purpose before the contrast. The parentheticals (MiniLM, real input/output matching) are dense but each earns its place by clarifying the distinction; slight density keeps it from a 5.

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?

With an output schema present and annotations covering the safety profile, the description supplies exactly what is missing: the similarity mechanism and the routing rule versus get_compatible_tools. Nothing needed to call the tool correctly is absent.

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 description coverage is 100% for both parameters (slug with examples, limit with default/max), so the schema carries the parameter burden. The description adds no syntax, format, or constraint detail beyond what the schema already states, so 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?

States a specific verb and resource ('find AI tools conceptually/philosophically similar to a given tool') and immediately names the mechanism, semantic embedding similarity of name and tagline, which distinguishes it from generic category matching. It also names the sibling get_compatible_tools it is not, so an agent can separate the two without opening a 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?

Explicitly routes the agent: 'Use this for tools like X questions, get_compatible_tools for what connects to X questions.' The when-to-use condition and the named alternative are both stated, leaving nothing to inference.

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