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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description earns credit for adding context beyond them: the data provenance ('from filings and releases'), the freshness limit ('latest quarter'), and a monetization constraint ('Quarterly history is paid') that tells the agent historical requests will not be served for free.

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?

Two sentences, front-loaded with the returned metrics and scope, with the paid-tier caveat placed last where it belongs. The long OEM enumeration is dense but functional rather than filler; 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?

For a no-required-parameter read tool with full schema coverage and no output schema, the description covers what is returned, which quarter, the source, and the paid boundary. The knowable gaps are minor – no explicit routing advice versus siblings and no mention of whether an empty oem returns all companies.

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?

With a single parameter at 100% schema description coverage, the schema already documents 'oem' as an optional company name filter; baseline 3 applies. The description adds indirect value by enumerating valid OEM names (Eaton, GE Vernova, Siemens Energy, ABB, Schneider, Vertiv, Powell, Caterpillar, Cummins, Trane), which hints at accepted filter values, but it never ties that list back to the parameter.

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?

States a specific resource (orders, revenue, backlog, book-to-bill, backlog growth), the exact scope (electrical, power and cooling OEMs, with named companies), and the freshness window (latest quarter). An agent immediately knows what comes back. It does not, however, distinguish itself from sibling data tools like get_lead_times or get_price_bands, so it stops short of a 5.

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?

Usage is only implied: 'latest quarter' tells the agent this is a current snapshot, and 'Quarterly history is paid' gates the historical use case. There is no explicit when-to-use statement, no prerequisites, and no named alternative among the sibling data tools. Adequate but leaves the agent to infer routing.

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