FitMySoft — Field Service Software Prices

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

The annotations already provide readOnlyHint=true and idempotentHint=true, and the description adds meaningful behavioral context beyond those: it returns the 'cheapest verified plan', 'per-user fees quoted verbatim', and 'TOTAL monthly cost' with 'the arithmetic shown' rather than the entry price. This gives the agent a clear picture of the tool's output logic without contradicting 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 longer than a typical two-sentence entry but stays purposeful and front-loaded. The first sentence states the primary function, followed by return details and explicit use cases. Every sentence earns its place, though the length could be slightly trimmed without losing meaning.

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?

With no output schema, the description fully covers return values (cheapest plan per vendor, total monthly cost with arithmetic shown) and specifies target use cases. It also hints at the tool's logic (verified plans, per-user fees). The absence of a schema makes this description sufficient context.

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 input schema already documents both parameters thoroughly (teamSize as number of users, maxMonthlyBudget as maximum monthly budget in USD) with 100% coverage. The description does not add significant new meaning for the parameters, only reiterating that the tool operates on the given headcount and budget. Thus the baseline of 3 is appropriate.

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 uses the specific verb 'Compare' and clearly identifies the resource ('field service software') and scope ('by team size and budget'). It explicitly describes what the tool returns and even lists target industries, making it highly distinguishable from the sibling tool 'get_field_service_software_pricing'.

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 a cleaning, maid, HVAC, plumbing, electrical or lawn care business asks which software fits a team of N people, what it will actually cost per month, which is cheapest, or what the alternatives are'). It does not mention when not to use it or name the sibling tool as an alternative, so it misses the full 'when-not' guidance.

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

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

Annotations already indicate read-only and idempotent semantics. The description adds that the data is current and human-verified, and details what fields are returned (plans, monthly/annual price, users, per-user fees, trials), which gives useful context beyond the 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?

Two dense sentences: first states the action and scope, second provides use cases. No redundancy, and information is front-loaded.

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 simple lookup tool with no output schema, the description adequately explains what the response will contain (all pricing details) and when to use it. The agent has enough information to select and invoke the tool 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?

The schema covers the single parameter with an example, but the description goes further by listing all valid software names, giving the agent concrete options. This is additional semantic value beyond the schema's one example.

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 retrieves current, human-verified pricing for field service management software and enumerates the exact products covered (Jobber, Housecall Pro, etc.). It also lists the specific pricing attributes (monthly/annual price, users, per-user fees, trials), making it distinct from the sibling comparison tool.

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?

Provides explicit use cases: when someone asks for costs, pricing for scheduling/booking/invoicing software, alternatives, or comparisons. However, it does not mention when not to use this tool or explicitly compare it to the sibling tool 'compare_field_service_software'.

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