semantic_search_activities

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

With no annotations, the description fully discloses behavior: it uses vector similarity, handles fuzzy/paraphrased queries, and returns shallow rows ranked by similarity. It could add read-only hint and cost/rate limits, but the core behavior is clearly stated.

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 sentences, no wasted words. The key information (usage condition, behavior, output) is front-loaded. Every sentence serves a purpose.

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?

Given 4 parameters and no output schema, the description provides adequate purpose and usage guidance but lacks parameter details and comprehensive return value specification. It states 'Returns shallow rows ranked by similarity' but doesn't explain what fields are in each row.

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 does not explain any of the 4 parameters (query, start, end, limit). While the parameter names are somewhat self-explanatory, the description fails to add meaning, such as format of query or date range constraints.

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?

The description clearly states 'Vector similarity search over activities' with a specific verb (search) and resource (activities). It distinguishes from keyword searches by specifying the method (vector similarity) and use case (fuzzy/paraphrased queries), which differentiates it from sibling tools like search_activities.

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 explicitly says 'Use only when keyword search fails — for fuzzy or paraphrased queries', providing clear when-to-use guidance. It implies when not to use (when keyword search works) but does not explicitly name alternative tools.

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