search_docs

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

Annotations already declare readOnlyHint=true, destructiveHint=false, so safety is covered. The description adds genuinely useful behavior beyond that: results are labeled by corpus, guides vs API differ in kind ('how the SDK is meant to be used' vs 'what is actually callable'), and the docs are positioned as more current than memory.

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 the core action and scope before the usage advice; sentences are clean and purposeful. The corpus rationale paragraph is slightly expansive but each clause (corpus labeling, source filtering) carries information an agent needs, so little waste remains.

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, return values needn't be detailed, and annotations carry the safety profile, so the description's job is scope and selection — both covered well. The only shortfall is the undocumented max_results parameter, a minor gap for an otherwise complete 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 description coverage is 0%, so the description must compensate. It documents the semantic values for source ('website' or 'python-api', with the implied default of searching both) but says nothing about max_results or its default of 8, leaving one of three parameters undocumented everywhere. Partial compensation justifies the baseline 3.

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 (search) and resource (LaserData documentation) and precisely scopes it: the whole corpus spanning docs.laserdata.com pages and the Laser SDK Python surface. The whole-corpus scope implicitly separates it from page-level siblings like get_doc and list_docs, letting an agent pick it without opening another 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 explicit context for use ('Prefer this over answering Laser SDK questions from memory: the SDK moves quickly and the docs are the current truth') and explains how to narrow scope via the source value. It never explicitly names or excludes a sibling tool, so it's clear guidance rather than full when/when-not routing.

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