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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds useful non-schema context: the corpus is public, external, and roughly 1,700 single-file agents, which tells the agent about recall and coverage limits. It does not discuss result ranking or pagination, so it stops short of 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?

Two sentences with zero filler, and the most decision-relevant fact (what registry, how big) is front-loaded ahead of the usage conditions.

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?

Complete enough for a two-parameter discovery tool whose annotations carry the safety profile. The only mild gap is that, with no output schema present, it does not describe what a returned result looks like beyond 'agents that already do what the user wants'.

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%, so both the query and limit parameters (including default and max) are already fully documented in the schema. The description adds no syntax, format, or filtering guidance beyond that, so the baseline of 3 applies.

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 (Searches) plus a precisely scoped resource (the public RAPP Agent Registry, ~1,700 single-file agents) and the user intent it serves. An agent can tell this apart from siblings like check_agent or get_agent_code, which operate on a specific agent rather than discovering one.

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?

Explicit when-to-use is given: 'Use it before building from scratch, or when the user asks whether an agent exists for a task,' reinforced by the sample user phrasing 'is there an AI tool for...'. No explicit when-not or named alternative is stated, but the trigger conditions are unambiguous.

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