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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds technical details: BGE-base-en embeddings, cosine similarity, 500-char windows, 200K char cap with truncation flagging. 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?

Two well-structured sentences. The first covers purpose and when-to-use; the second adds technical specifics. Every sentence provides distinct value with no redundancy.

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 no output schema, the description explains return structure: top-N passages with character offsets and similarity scores. Covers caps, truncation, and pairing with another tool. Sufficient for an agent to invoke and interpret results correctly.

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% with good descriptions. The description reinforces the intended usage ('Pass the text you already pulled...') and provides explicit query examples (e.g., 'drug interactions with warfarin'). Adds clarity on limit default and range beyond 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 clearly states 'Semantic search INSIDE a fetched record' and explains the use case. It distinguishes from sibling tools like ask_pipeworx_grounded by showing how they pair, making the tool's specific role unambiguous.

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?

Explicitly advises using when a record is too large for the prompt, saving context. Mentions pairing with ask_pipeworx_grounded. Lacks a direct 'when not to use', but the context strongly implies alternative if the record fits in the prompt.

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