Find Data by Concept

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description goes beyond that by specifying the return structure (ranked planes: FIELDS, VALUES, DOCUMENTS, PASSAGES) and adding operational context: 'Read-only, no LLM cost.' It also notes that results are 'ready handles for the next call,' which tells the agent the output is directly reusable. No contradiction with 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?

The description is long but every sentence earns its place, organized with bolded section headers (USE WHEN, NOT FOR, ARGS, RETURNS) that make scanning easy. The core purpose is front-loaded in the first sentence, and the rest provides structured, non-redundant detail. No filler or tautology.

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 is complex (semantic retrieval across multiple planes, no output schema), and the description fully compensates. It explains what each return plane contains, how to interpret the results (ranked, with handles for subsequent calls), and the hard scope semantics of document_ids. With no output schema, this description carries the full burden and meets it. Also covers safety via annotations and adds the 'no LLM cost' note, which is operationally important.

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%: each parameter already has a description in the schema (query, top_k, document_ids). The description reinforces these by restating query as 'the concept, in the user's words,' top_k default as 10, and document_ids as a hard scope. This adds minor nuance beyond the schema (e.g., 'hard scope' and default) but largely repeats it, so it stays above baseline 3 without reaching 5.

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 ('locate') and resource ('real data behind a natural-language concept'), then immediately explains the mechanism (semantic + lexical retrieval) and the scope (fields, values, documents, passages). It explicitly distinguishes itself from siblings by naming talonic_list_fields / talonic_search and stating when those fall short, so an agent can select it unambiguously.

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 provides a dedicated 'USE WHEN' section that lists three concrete triggers (unsure which field holds a concept, sibling tools returned empty/ambiguous, answer may live in prose) and a 'NOT FOR' section naming two alternatives (talonic_field_values, talonic_filter). This is explicit, actionable routing guidance with no room for inference.

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