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

The description discloses rich behavioral details beyond the annotations: returns top-N passages with character offsets and similarity scores, enables quote verification, uses BGE-base-en embeddings with cosine similarity over 500-char overlapping windows, and enforces a 200K-char cap with truncation flagged. This far exceeds the minimal readOnly/idempotent hints.

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 four sentences, each dense with purpose: the first defines the core action, the second specifies use cases and output, the third names a sibling integration, and the fourth gives technical constraints. The most important information is front-loaded, and no sentence is wasted.

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 not having an output schema, the description fully explains what the agent can expect (passages, offsets, similarity scores). It also covers input size limits, truncation behavior, and the embedding approach. For a tool with only three parameters, this is complete and self-sufficient.

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 the baseline is 3; however, the description adds meaning by explaining that 'text' is 'the text you already pulled' and gives concrete query examples ('supply-chain risk', 'drug interactions with warfarin'), helping the agent craft effective queries. It also clarifies that text is the source to search within, not a general input.

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' — a specific verb and resource — and clearly distinguishes this from sibling tools by emphasizing that it operates on already-fetched text rather than the wider corpus. It also names a complementary tool (ask_pipeworx_grounded), reinforcing its unique role.

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?

Explicit guidance is provided: 'Use when the record is too big to cram into the prompt' and it explains how this tool saves context. It also pairs with ask_pipeworx_grounded, giving a concrete alternative workflow and making the when-to-use vs. alternatives clear.

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