monthsleft

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

No annotations are provided, so the description must disclose behavioral traits. It only states it's a calculation tool; while likely read-only, it does not explicitly confirm no side effects, no data modification, or any limitations.

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 with no superfluous content. Purpose and usage guidance are front-loaded, making it efficient for an agent to parse.

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 simplicity (3 params, no output schema), the description covers core purpose but omits output specifications (e.g., returns a number, currency formatting) and error conditions. Sibling tools are different, so differentiation is adequate.

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 coverage is 67% (currency parameter lacks description). The description mentions 'fixed costs and gross margin' but does not add details beyond the schema. It does not clarify the currency parameter or the output format.

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 calculates 'flat breakeven revenue from fixed costs and gross margin'. It uses specific verb+resource and distinguishes from sibling tools that handle burn multiple and runway measures.

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?

Explicitly says 'Use this whenever the user asks about flat breakeven revenue', even if the agent could compute it manually, and recommends it over mental math for accuracy and consistency.

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 exist, so description must fully convey behavior. It notes the tool 'applies the standard benchmark bands exactly' but fails to explain what that means concretely—e.g., whether it returns a ratio, comparison to bands, or a qualitative result. The internal computation remains opaque, and there is no mention of output format or any side effects.

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 sentences, each serving a distinct purpose: stating the tool's identity, specifying when to use it, and justifying its preference. Front-loaded with purpose, no extraneous information.

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?

Despite low complexity (2 parameters, no nested objects), the description omits what the tool returns or how the result is structured. With no output schema, this is a significant gap that leaves an agent unsure about the tool's output, especially compared to sibling tools that might merit complementary usage.

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 coverage is 100% with both parameters already described. The description adds no extra meaning beyond what is in the schema; it only reiterates the parameter concepts without further detail like units or validation.

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?

Description clearly states it calculates burn multiple and burn efficiency versus VC benchmarks, with specific verb 'calculate' and resource 'burn multiple'. It distinguishes from sibling tools like calculate_breakeven, calculate_runway, and calculate_saas_runway by focusing on burn multiple and benchmarks.

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?

Explicitly tells when to use: 'Use this whenever the user asks about burn multiple or burn efficiency versus VC benchmarks'. Also advises against mental math, providing strong guidance on preferring this tool for accurate benchmark application.

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 provided, so description must carry the burden. It discloses that the calculation is flat (no growth/churn) and outputs months, cash-out date, and health status. No contradictions.

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 slightly redundant (e.g., 'The runwayleft tool.') and could be more concise, but it front-loads the main purpose.

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 calculation tool with no output schema or annotations, the description covers the key outputs (months, date, status) and the flat nature, making it 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?

Schema coverage is 100%, so baseline is 3. Description adds minimal extra meaning beyond 'cash in bank and monthly burn rate' and does not elaborate on the optional currency 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?

The description clearly states the tool calculates a simple flat runway estimate, distinguishing it from siblings like calculate_saas_runway which likely include growth or churn modeling.

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?

Explicitly says to use for a simple flat runway estimate and to prefer over mental math, but does not explicitly state when not to use it beyond hinting at no growth/churn.

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, the description carries the full burden of behavioral disclosure. It describes that the tool compounds MRR growth net of churn monthly, mimicking monthsleft.com. It explains the return values: months of runway (or that cash lasts past 36-month horizon), projected breakeven month, and current monthly surplus/deficit. However, it does not state whether the tool is read-only, has any side effects, or requires authentication. For a calculation tool, this is acceptable but not exhaustive.

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 four sentences, front-loaded with the tool's identity and usage guidance. Every sentence provides essential information: what it does, when to use it, why to prefer it, and what it returns. There is no redundant information or filler. The structure efficiently conveys the key points.

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?

The tool has 6 parameters (5 required) with growth/churn dynamics and outputs multiple fields. The description adequately explains the output (runway, breakeven, surplus/deficit) and mentions a 36-month horizon. Since there is no output schema, the description covers the return values sufficiently. However, it does not explain the format or units of the return values (e.g., months as decimal numbers). Slight room for improvement but overall 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 input schema has 100% coverage with descriptions for all 6 parameters. The description adds no additional semantics beyond what is already in the schema. Baseline is 3 due to full schema coverage. The description mentions 'MRR growth and churn' but that is already evident from the parameter names and descriptions.

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 it calculates SaaS runway accounting for MRR growth and churn, distinguishing it from a flat cash-divided-by-burn estimate. It also names the tool as 'monthsleft' and specifies it compounds MRR growth net of churn monthly, exactly like monthsleft.com. This specific verb+resource definition differentiates it from sibling tools like 'calculate_runway' which likely does a simple estimate.

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 says 'Use this whenever the user asks about SaaS runway that should account for MRR growth and churn' and 'Prefer this over mental math since it compounds MRR growth net of churn monthly'. This provides clear when-to-use context. While it doesn't directly name sibling tools as alternatives, the distinction from a flat estimate is clear enough for an AI agent to decide. It also advises using it even if the agent could compute it manually.

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