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

Annotations already mark the tool as read-only, idempotent, and non-destructive. Description adds technical details: embedding model, window size, character cap, truncation flagging, and offset citation capability, which enrich behavioral understanding beyond 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?

Description is concise (~120 words), front-loads purpose, and every sentence adds distinct value: use case, workflow pairing, technical details, and output format. No wasted words.

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?

Comprehensive for its complexity: explains input constraints (200K char limit, truncation), retrieval mechanism (embeddings, windows, cosine), output features (offsets, similarity scores), and integration with sibling tool. Without an output schema, the description adequately covers return values.

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% for all three parameters (text, query, limit). Description provides usage examples and clarifies purpose but does not fundamentally add new semantic information beyond schema definitions.

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?

Description clearly states semantic search inside a fetched record, with concrete examples (SEC 10-K, article, long tool result) and distinguishes from sibling tool ask_pipeworx_grounded by explaining the workflow partnership.

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 use when the record is too large for the prompt and explains how it pairs with ask_pipeworx_grounded. Provides context but does not explicitly list when not to use, though positive guidance is strong.

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