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

Annotations already declare readOnly=true, idempotent=true, destructive=false, so the safety profile is covered. The description adds useful behavioral context that the query is interpreted in plain language with fuzzy-ish matching, but says nothing about result ordering, result count, or pagination.

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 with the core purpose front-loaded and an illustrative example appended; nothing is redundant or padded.

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?

There is no output schema and no annotations about returns, so the description should at least indicate what comes back (a ranked list of matching patterns, presumably) and whether results are paginated. For a one-parameter search tool it is adequate, but the result-side context 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 description coverage is 0% for the single 'query' parameter, so the description must carry the load. The worked example ('gradient headline' → A10 Gradient Text Headline) usefully conveys that input is free-form natural language, but it leaves matching rules, multi-term behavior, and case handling unexplained.

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 ('Plain-language search across the library') and clarifies the matching style as natural language rather than exact match. It does not explicitly distinguish itself from close siblings like list_patterns or get_pattern, so it stops short of a 5.

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?

The example shows how a query looks but never says when to choose this over list_patterns (browse all) or get_pattern (fetch one known item). No prerequisites, exclusions, or alternatives are named, leaving selection to inference.

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