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

Annotations cover the safety profile (readOnlyHint=true, openWorldHint=false), but the description adds real value by disclosing the compact return format line-by-line and the read/write tagging of each result. There is no output schema, so this preview is doing genuine work. It stops short of stating result limits or how large a full listing can get.

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 short sentences, both front-loaded with the most decision-relevant information: the use case first, then the return shape and the next call. No filler and nothing an agent must read twice.

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 one-parameter read-only discovery tool with no output schema, the description supplies the missing piece (what a result looks like) and the chaining rule. Only minor gaps remain, such as whether the full listing is paginated or capped.

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% and the single query parameter is fully documented there, including the no-query/no-match behavior of listing everything. The description adds nothing about the query beyond restating the discovery intent, so the baseline 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?

Names a specific verb (find) and resource (Shiko's map tools), scopes it to the discovery case ("when you don't know the name you need"), and previews the exact return shape (name [read|write] summary). It also routes to describe_tools as the follow-up, so an agent can place it in the search→describe→run sequence 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?

Gives an explicit when-to-use condition (you don't know the tool name), which implicitly excludes the case where the name is known, and names the next tool to call for arguments. The workflow handoff to describe_tools is spelled out rather than left to inference.

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