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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial extra behavior: identifier normalization and exact-match-first ordering surfaced via `match: identifier`, per-area read scopes with unreadable areas reported in `skipped`, and `href` pointing to the dashboard screen each hit opens. No contradictions with the read-only annotation.

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?

Front-loads the core purpose and the dashboard analogy before the taxonomy, and every clause carries information rather than filler. The long parenthetical identifier lists are dense but each one tells the agent something it would otherwise have to guess at.

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?

No output schema exists, so the description must explain return shape — and it does, covering `match: identifier`, `skipped` for scope gaps, and `href` per hit. For a two-parameter federated search tool that is everything an agent needs to call it and interpret the response correctly.

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 q and limit are already documented, and the description adds real semantics on top — it specifies what q accepts (GTIN, NDC, GLN, lot, chip ID, GS1 Digital Link, element string, EPC URN) and that such input is parsed. The 300-character cap and the limit default/max remain schema-only, which is fine given full coverage.

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?

Opens with a specific verb and resource ("Search this company's records") and then enumerates exactly which entity types are covered, including the identifier fields matched in each. The dashboard-search-bar analogy plus the explicit list makes it immediately distinguishable from narrow siblings like list_products or find_unit.

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?

Gives a concrete usage rule ("Paste an identifier as-is") with the formats that trigger parsing, and explicitly routes question-answering to ask_agent. It also supplies an interpretation rule — don't read an empty group as "none" when the area appears in `skipped` — which is exactly the kind of when/when-not guidance an agent needs.

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