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

Annotations already declare this is a safe, idempotent read with no external side effects, so the description focuses on what annotations cannot express: the response fields (page, website, category, description) and the ranking bias disclosure that "featured" listings are paid placements. That paid-placement caveat is genuinely useful for an agent weighing results, though ranking logic beyond that is unstated.

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?

Two front-loaded sentences covering purpose, examples, return shape, and the featured caveat, with no filler. The paid-placement note could arguably be folded into the return sentence, but its separation makes it stand out.

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 no output schema, the description correctly summarizes return fields and adds the sponsored-result caveat, which is what an agent most needs to interpret results. Minor gaps remain around pagination and how limit interacts with ranking, but nothing essential to calling the tool is missing.

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 67% and the schema itself explains both q (empty lists newest, featured first) and category. The description adds only phrasing guidance for q via example queries and says nothing about the limit parameter's role. Baseline 3 is appropriate given the schema does most of the work.

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 ("Search the EveryAI directory for AI tools") and reinforces it with two concrete example queries. It does not explicitly distinguish itself from siblings like get_tool or list_categories, leaving that differentiation to the names alone.

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?

Gives a clear usage context — describe the task in natural language rather than an exact tool name — and the schema covers the empty-query fallback for browsing newest tools. It offers no explicit exclusions or pointers to alternatives such as get_tool for a known tool, so an agent must infer the boundary.

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