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

Given annotations already state readOnlyHint, openWorldHint, idempotentHint, and non-destructive, the description adds significant behavioral detail: character offsets, similarity scores, BGE-base-en embeddings, cosine over 500-char overlapping windows, and a 200K char cap with truncation flagging. This goes well beyond the annotations and gives the agent concrete expectations.

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 a single, well-structured paragraph that front-loads the core purpose and then packs each sentence with useful details: return format, use case, pairing, embedding algorithm, and limits. No sentence is wasted, and the length is appropriate for the tool's complexity.

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 tool has no output schema, but the description covers what the agent will receive (top-N passages with offsets and similarity scores). It also discloses truncation behavior, algorithm choice, and workflow pairing, making it fully self-contained for an agent to decide when and how to invoke it.

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 practical examples for text (SEC 10-K body, article, long tool result) and for query (supply-chain risk, fiscal year revenue), plus clarifies that text is something already pulled. This enriches the parameter understanding beyond the schema fields.

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 opens with 'Semantic search INSIDE a fetched record,' giving a specific verb, resource, and scope. It clearly distinguishes from siblings like search by emphasizing the input is already-fetched text, and it references ask_pipeworx_grounded as a complementary tool.

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?

It explicitly says 'Use when the record is too big to cram into the prompt' and explains the benefit of saving context and returning only relevant passages. It also pairs with ask_pipeworx_grounded to show the intended workflow, though it does not explicitly list exclusions or when not to use it.

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