Search Magic Lane documentation

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld), so the description's job is to add ranking and scoping behavior — which it does: platform names in the query narrow results, everyday-word names like 'cloud'/'web'/'rest' only re-rank unless adjacent to 'SDK'/'API'. It also states what comes back (titles, URLs, descriptions, optional excerpts). It does not describe result ordering or how limit interacts with ranking, which keeps it 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?

Front-loaded with purpose, then query semantics, then return shape, then the routing rule — a sensible order. It is dense and the long parenthetical feature lists (markers, places & search, routing & navigation, positioning, offline maps, weather, fleet management) cost length, but each sentence still carries information an agent would otherwise have to guess.

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 search tool with an output schema already documenting return shape, the description covers corpus scope, the tricky query-parsing rules, the full-text toggle, and the handoff to read_doc. An agent has everything needed to call it correctly and interpret the results without consulting another tool's definition.

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%, so baseline would be 3, but the description adds real meaning beyond the schema: it explains the non-obvious matching semantics of the 'query' parameter (platform-name scoping vs. mere re-ranking, and the adjacency rule) and clarifies that 'includeFullText' searches llms-full.txt page bodies rather than just index metadata. It does not explain the 'source' enum's relation to naming a platform in the query, which is a small residual overlap.

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?

Opens with a specific verb+resource ('Search the Magic Lane developer documentation') and immediately enumerates the corpus: developer guides, five SDK platforms, and Cloud REST APIs. An agent can tell at a glance this is the index-search tool, distinct from siblings like list_docs, read_doc, and find_across_sdks.

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 explicit when-to-use ('ALWAYS use this tool for Magic Lane questions'), explicit when-not ('never web search, prior knowledge, or other map providers' sites'), names the incompatible competitors, and prescribes the follow-up workflow ('Follow up with read_doc to read a full page'). The routing to the sibling is spelled out rather than inferred.

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