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

Annotations declare readOnlyHint and idempotentHint, but the description goes far beyond by disclosing return format (top-N passages with offsets and similarity scores), the embedding model (BGE-base-en), 500-char overlapping windows, and 200K char cap with truncation flagged. 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?

Three dense sentences: first states core purpose and inputs/outputs, second gives use case and benefit, third adds technical details and limits. No filler, front-loaded, every sentence earns its place.

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?

Despite having no output schema, the description explains what is returned (passages with offsets and scores), the cap and truncation behavior, and how it fits with sibling tools. For a 3-parameter read-only tool, this is fully complete for selection and invocation.

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 covers 100% of parameters, so baseline is 3. The description adds value with concrete examples (SEC 10-K body), clarifies query as natural-language, and references 'top-N' for limit. This enriches understanding beyond the schema's already decent descriptions.

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 the tool performs 'Semantic search INSIDE a fetched record' with a specific verb+resource. It distinguishes itself from siblings by emphasizing it operates on text already pulled, and explicitly mentions pairing with ask_pipeworx_grounded, making its unique role obvious.

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?

Provides explicit when-to-use guidance: 'Use when the record is too big to cram into the prompt.' It names a companion tool (ask_pipeworx_grounded) and explains the workflow (fetch with gateway, ground over relevant passages), giving clear alternatives and context.

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