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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. Description adds critical behavioral traits: embedding model (BGE-base-en), windowing (500-char overlapping), truncation at 200K chars with flag, and return details (character offsets, similarity scores).

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 front-loaded with purpose and use case. It is slightly verbose but every sentence adds value (e.g., details on pairs, embedding, truncation). Could be slightly tighter, but structure is logical.

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 fully explains return format (passages with offsets and scores). It also covers input constraints (200K char cap, truncation flag) and technical details (embedding model, window size). No significant gaps.

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 baseline is 3. Description adds value by providing examples for query (e.g., 'supply-chain risk') and clarifying text as 'document text to search inside (max ~200K chars)'. While schema already covers limits and defaults, the examples and context push it above baseline.

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 uses specific verbs and resources: 'Semantic search INSIDE a fetched record.' It clearly distinguishes from siblings by naming ask_pipeworx_grounded and explaining when to use search_within vs the alternative.

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 states when to use: 'when the record is too big to cram into the prompt.' It also explains what it avoids ('saves context, returns only relevant passages') and pairs with ask_pipeworx_grounded for grounded retrieval.

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