calculate_inventory_value

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'returns total value, item count, average value, and optional breakdown,' which covers output behavior. However, it lacks critical details like whether this is a read-only operation, performance implications of grouping, rate limits, or authentication requirements, leaving significant gaps for a tool with 11 parameters.

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 efficiently structured in two sentences: the first states the purpose and scope, and the second details the return values and grouping options. Every phrase adds value without redundancy, making it front-loaded and appropriately sized for the tool's complexity.

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 the tool's complexity (11 parameters, no annotations, no output schema), the description is moderately complete. It covers the purpose, filtering/grouping scope, and return values, but lacks behavioral details (e.g., read-only status, performance) and doesn't compensate for the absence of an output schema, leaving the agent with incomplete context for invocation.

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?

The description adds some value by mentioning 'comprehensive filtering and grouping' and listing breakdown options (e.g., 'by category, location, account, inventory type, or status'), which aligns with the 'group_by' parameter. However, with 100% schema description coverage, the input schema already documents all 11 parameters thoroughly, so the description doesn't significantly enhance parameter understanding beyond the baseline.

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 states the tool's purpose: 'Calculate total inventory value with comprehensive filtering and grouping.' It specifies the verb ('calculate') and resource ('total inventory value'), making the function unambiguous. However, it doesn't explicitly differentiate from siblings like 'calculate_account_metrics' or 'calculate_sales_totals' beyond the resource focus, preventing a perfect score.

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 provides no guidance on when to use this tool versus alternatives. It mentions 'comprehensive filtering and grouping' but doesn't specify prerequisites, compare to siblings (e.g., 'calculate_account_metrics'), or indicate when not to use it. This leaves the agent without contextual usage cues.

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