FindingLeads

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

With no annotations provided, the description carries the full burden and uses it well. It discloses that the result is a band rather than a single number, and that omitting a real call volume yields an unquantified result rather than a fabricated one—critical honesty for an agent.

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?

Three short, focused sentences front-load the core purpose and follow with output behavior and edge-case handling. Every sentence adds meaningful information with no fluff or repetition.

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 two-parameter estimation tool, the description covers purpose, inputs, output form, and the no-volume edge case. Even without an output schema or annotations, an agent has enough to call it correctly and interpret the result.

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 already covers both parameters fully, so the baseline is 3. The description adds value by explaining what happens when calls_per_month is absent ('returns unquantified rather than inventing one'), which clarifies the optional parameter's practical semantics beyond the schema.

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 states a specific analytical resource: the monthly cost of unanswered calls for a home-service business, expressed in extra jobs and dollars. It also clarifies important output semantics (a band, not a point estimate), which makes it clearly distinct from siblings like get_offer and list_trades.

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 implies the tool is used when a cost estimate for missed calls is needed, and it identifies the required inputs (trade and monthly call volume). However, it gives no explicit guidance on when to choose this tool over the siblings or any exclusions.

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?

No annotations are provided, so the description carries the burden. It discloses that the tool returns information about the service, cost, and next step. It doesn't mention whether it's read-only, but for an informational tool with no parameters, the risk is low. It could be more explicit about what the output looks like, but the description is adequate.

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?

One sentence, front-loaded with the key content (what, cost, next step), and ends with a clear usage directive. No wasted words.

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 0-parameter informational tool with no output schema, the description is complete enough. It tells the agent what content to expect and when to use it. It could mention the format of the output, but that's minor for this simple tool.

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 tool has 0 parameters, so the schema is trivially complete. The description doesn't need to explain parameters. Baseline 4 is appropriate for a no-parameter tool.

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 states a specific purpose: it explains what FindingLeads does, its cost, and the next step. It is clear about the resource (FindingLeads service) and the content of the response. It doesn't explicitly differentiate from siblings, but the content is distinct enough from estimate_missed_call_cost and list_trades.

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 gives a clear usage context: 'Read this before describing the service to anyone.' This tells the agent when to use it (before describing the service). It doesn't explicitly name alternatives or exclusions, but the context is clear enough for a 0-parameter informational tool.

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?

With no annotations provided, the description carries the behavioral burden. It conveys the data content but does not explicitly state that this is a read-only listing operation, how results are ordered, or what exact structure is returned. The read-only nature is strongly implied by the name, making this minimally adequate.

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 a single compact sentence with no filler words. It could be more action-oriented by starting with 'Lists...', but it remains appropriately sized and readable.

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 parameterless reference-listing tool, the description names every relevant output attribute: typical job value, repair/project classification, and unanswered-call frequency. It does not describe return formatting, but with no output schema and such a simple operation, it is reasonably complete.

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 tool has zero parameters and 100% schema coverage, so there are no parameter semantics to document. The baseline of 4 applies because no parameter burden exists.

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 resource: the home-service trades FindingLeads serves, and enumerates the attributes included for each trade. It stops short of an explicit verb-phrase like 'Lists all trades' and does not name sibling tools, so it is clear but not maximally differentiated.

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?

No guidance is given about when to use this tool versus estimate_missed_call_cost or get_offer. The usage is only implied by the word 'list' in the tool name and the reference-style content, with no explicit when-to-use or exclusions.

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