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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the bar is lower. The description adds substantial behavioral context: BGE-base-en embeddings, cosine similarity over 500-char overlapping windows, a 200K-char cap with truncation flagging, and that each passage includes an offset for verbatim verification. This goes well beyond annotations to disclose concrete technical behavior.

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 compact yet information-dense. Three sentences cover purpose, use-case, pairing, and technical details without fluff. Every clause earns its place, and the most critical information (what the tool does) is front-loaded.

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?

For a complex tool with no output schema, the description is remarkably complete. It covers what the tool does, when to use it, how it pairs with another tool, the technical embedding/offset mechanism, and input/output behavior. The agent would know exactly what to expect 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 description coverage is 100%, so baseline is 3. The description adds meaning beyond the schema: it gives concrete examples for 'text' (SEC 10-K body, article, long tool result) and for 'query' (supply-chain risk, fiscal year 2024 revenue, drug interactions). It also explains that 'limit' controls the top-N passages returned. This enhances understanding of parameter usage.

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 a specific verb and resource: 'Semantic search INSIDE a fetched record.' It clearly identifies what the tool does, including input (text already pulled) and output (top-N passages with character offsets and similarity scores). It also distinguishes itself from siblings by explicitly pairing with ask_pipeworx_grounded and focusing on search within a single fetched record rather than broader retrieval.

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 provides explicit usage guidance: 'Use when the record is too big to cram into the prompt' and explains the trade-off (saves context, returns only relevant passages). It also names a sibling tool (ask_pipeworx_grounded) and describes the complementary workflow: fetch with the gateway, then ground over relevant passages. This gives clear when-to-use and how-it-fits guidance.

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