Full-text search (client-side)

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

With no annotations, the description bears full responsibility. It discloses that the tool paginates, strips HTML, matches locally, and returns snippets. It also mentions API budget consumption. It does not detail performance implications or potential failure modes, but covers the key behaviors.

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?

The description is two sentences, front-loading the purpose and mechanism, then cost advice. No wasted words, each sentence adds value. Ideal length.

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?

The description explains the core search mechanism and cost, but omits details on parameter usage for 6 of 8 parameters. No output schema, so return format is barely mentioned ('snippet'). More guidance on parameter semantics would improve completeness.

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 only adds guidance for 'types' and 'max_pages_per_type'. Other parameters like 'query', 'campaign_id', 'per_page', 'limit', 'case_sensitive', and 'regex' are left unexplained. The description adds limited value beyond the schema.

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 specifies the action 'search' and the resource 'body text of entities', and explains the method (paginating, stripping HTML, matching locally). It distinguishes from sibling tools like kanka_search, which likely does a different kind of search.

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 explicit guidance: 'Costs API budget — narrow types and lower max_pages_per_type to keep it cheap.' It warns about cost and suggests parameter tuning. It does not explicitly state when not to use, but the cost implication implies alternatives might be preferred for small searches.

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