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

With no annotations provided, the description carries the full behavioral disclosure burden and does so well. It discloses conditional data ('when set,' 'when those hosts are attributed'), empty-value handling ('zeros when empty'), and account-type-specific behavior ('On a developer-account pool...'). It lacks exact response shape or rate-limit details, but for a read-only snapshot the key behavioral traits are covered.

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 opening phrase 'Company spend snapshot in one read' front-loads the core purpose, followed by a dense enumeration of returned metrics and a clear use-case sentence. It is somewhat long and packs many conditional clauses into one flowing sentence, but there is little redundancy or filler.

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?

Given there is no output schema, the description compensates by thoroughly listing the returned dimensions, conditional cases, and the intended use scenario. It covers edge cases like empty values and developer-account variants. It could be more explicit about the exact response structure, but for an agent selecting and invoking the tool, the information is largely 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 input schema already fully documents all three parameters, including defaults. The description does not add meaningful parameter-level semantics beyond what the schema states; it focuses on output content rather than how period or breakdown_by change the returned data.

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 clearly identifies the tool as a read-only company spend/credit usage snapshot and enumerates the specific returned data: remaining FOS credits vs plan limit, reset date, $ cap, Grok mix, hosting, and true inference $ on developer pools. The resource ('credit usage') is unambiguous and distinct from sibling tools like get_financial_summary or get_cash_position.

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?

The description explicitly states when to use the tool: 'Use when checking remaining credits, burn vs cap, or Grok mix.' This provides clear context for the intended scenario, though it does not name alternative tools or describe when not to use it, stopping short of a full 5.

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