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 indicates the tool performs a calculation, which is read-only, but does not explain output format, side effects, or any constraints. Adequate but minimal for a safe operation.

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 three concise sentences, each providing distinct value: defining the tool, specifying usage context, and justifying preference. No redundancy or unnecessary details.

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 and lack of output schema, the description covers purpose and usage but omits the return value format and any edge cases. The optional currency parameter lacks elaboration, reducing completeness for a parametric 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?

Schema description coverage is 67%, with two parameters documented in the schema. The description adds no additional meaning beyond the schema, such as clarifying the currency parameter's purpose or format. Baseline score applies as the description does not enhance parameter understanding.

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 is a breakeven tool for calculating flat breakeven revenue from fixed costs and gross margin. It specifies the exact metric and inputs, and distinguishes itself from sibling tools by targeting a specific financial concept, though it does not explicitly contrast with siblings.

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 advises using this tool 'whenever the user asks about flat breakeven revenue' and recommends it over manual calculation for accuracy. This provides clear context, though it lacks explicit when-not or alternative tool suggestions.

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?

Discloses the key behavioral trait of applying standard benchmark bands exactly, but doesn't mention output format or side effects. Since no annotations are provided, the description carries the full burden and is largely 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?

Two concise sentences with no filler, front-loaded with the tool's purpose and usage guidance.

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?

Complete enough for a simple two-parameter calculation tool, though it lacks output description. The sibling tools and no output schema are acceptable given the tool's straightforward nature.

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 descriptions for both parameters; the description adds no extra meaning beyond what the schema already provides, meeting 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 it calculates burn multiple for VC benchmark comparison, distinguishing it from sibling tools like calculate_breakeven and calculate_runway.

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 this tool (when burn multiple or efficiency is asked) and why to prefer it over mental math due to exact benchmark bands.

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?

Discloses the core outputs (months, cash-out date, health status) but lacks details on health status interpretation or edge case behavior (e.g., negative burn). No annotations exist, so description carries full burden; it is mostly adequate 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?

Two concise sentences with a clear front-loaded usage statement. Every sentence adds value: identifies the tool, explains usage context, and lists outputs.

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 no output schema, the description adequately lists key outputs (months, cash-out date, health status). However, it could specify exact format types for outputs. Overall sufficient for a simple tool with only 3 parameters.

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% and descriptions are already clear. The tool description reinforces parameters by mentioning 'cash in bank' and 'monthly burn rate', but adds no new semantic details beyond the schema. Baseline 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 clearly states the tool calculates months of runway, cash-out date, and health status from cash and monthly burn. It distinguishes itself from sibling tools like calculate_saas_runway by specifying 'simple flat runway estimate (no growth or churn modeling)', making its purpose unique.

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 advises using this tool for simple estimates, even over manual calculation, implying when to prefer it. Contrasts with more complex modeling tools, providing clear context for when not to use it.

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, description carries the burden. It explains that it compounds MRR growth net of churn monthly, like monthsleft.com, and lists return values. No destructive behavior is relevant; disclosure 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?

Description is concise with 5 sentences, front-loaded with the tool's alias and usage guidance. Every sentence adds value, no unnecessary 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 calculation tool with no output schema, description adequately covers expected returns (runway, breakeven, surplus/deficit) and the 36-month horizon. Could mention more edge cases but remains complete enough.

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 value by explaining the compounding logic (growth net of churn) beyond the individual parameter descriptions, enhancing understanding of their interaction.

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 that the tool calculates SaaS runway accounting for MRR growth and churn, distinguishing it from flat estimates. It specifies outputs like months of runway, breakeven month, and surplus/deficit.

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 states when to use ('whenever user asks about SaaS runway that should account for MRR growth and churn') and contrasts with simple mental math. Does not explicitly mention when not to use or name sibling tools, but context is clear.

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