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

Annotations already carry readOnlyHint=true and openWorldHint=false, so safety is covered. The description goes well beyond annotations by disclosing the matching algorithm (over title, description, section, slug), the lack of word-segmentation for zh/ja/th, index regeneration on deploy, and the presence of per-language counts in _meta. No contradiction with annotations.

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?

Four dense but purposeful sentences: scope, return fields, matching behavior, and index freshness. Every sentence earns its place, and the most decision-relevant caveat (not semantic search) appears early. No redundancy with schema or annotations.

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 no output schema, the description specifies the exact return fields (title, url, section, language, summary), covers the main matching caveats, and tells the agent where to find live document counts. Given the tool's complexity (24 languages, substring matching, edge cases), nothing essential 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 coverage is 100%, so the baseline is 3. The description adds meaningful behavior beyond the schema: it explains that query is matched as a substring/keyword, that zh/ja/th are treated as a single unsegmented substring, and that unrecognized language codes are skipped rather than failing. These nuances help an agent use the parameters correctly.

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 ('Anahana's wellness content'), enumerates content categories and language coverage. The scope is clear and distinct from siblings: it searches across content broadly rather than retrieving a single article (get_article) or performing a specialized angel-number lookup (lookup_angel_number).

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 description gives clear context for when to use the tool: keyword/substring search over wellness content in 24 languages. It explicitly warns that matching is NOT semantic search, which prevents a common misuse. However, it does not name sibling tools or state 'use get_article when you already have an article ID,' leaving some exclusion logic implicit.

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