nestegg-calculators

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

Annotations already declare readOnlyHint and idempotentHint. The description adds the formula but does not elaborate on edge cases, return format, or other behavioral details beyond the annotation scope.

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, front-loaded sentence that conveys the core function without any redundant words or structure.

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 financial calculation tool with a known output schema, the description is sufficiently complete. It explains the calculation clearly, though it could mention the optional dayCountBasis default.

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 has 100% coverage with parameter descriptions. The description adds the overall formula context but does not significantly enhance understanding beyond the schema's parameter 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 the tool calculates accrued interest since the last coupon, using a specific formula. It distinguishes itself from sibling financial tools like bond-price or current-yield.

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 usage for accrued interest calculation but provides no explicit guidance on when to use versus alternatives, no exclusions, and no context about prerequisites.

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. Description adds no additional behavioral context beyond the calculation. No mention of rounding, error handling, or constraints.

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?

Extremely concise: two sentences that directly state purpose and scale. No filler, front-loaded with 'After-tax yield'.

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 output schema exists and simple transformation, description is largely complete. Lacks mention of output format or edge cases, but not strictly necessary for this 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 provides clear descriptions for both parameters. Description adds value by clarifying 'Percents in and out,' ensuring users input percentages rather than decimals.

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 the tool calculates after-tax yield by reducing yield by tax rate, and specifies inputs/output are in percent. Distinct from financial sibling tools.

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 explicit guidance on when to use vs alternatives. Implicit for basic arithmetic tool, but siblings include similar concepts like tax-equivalent-yield, so more guidance would help.

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 indicate read-only and idempotent. Description adds important behavioral details: returns numbers and schedules, no advice, and explains pagination for monthly output. Enhances transparency beyond 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?

Concise and front-loaded with core purpose. Effectively conveys key features and output options in two sentences. Minimal waste, though the detail of output options could be shortened.

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 high parameter count and complexity, description covers core behavior and output types. However, it omits mention of input modes (term vs payment) and other parameters needed to use the tool, relying heavily on the schema. Adequate but not comprehensive.

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 has 100% parameter description coverage. The tool description adds minimal new information beyond schema—only elaborates on the 'detail' parameter which is already well-documented in the schema. Baseline score applies.

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 'monthly loan amortization schedule and summary' with specific features (extra principal, rate-fixed period) and output options. Effectively distinguishes from siblings like 'loan-payoff' which focus on payoff date.

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?

Implicit use guidance: intended for loan amortization calculations with extra payments and rate steps. No explicit when-to-use or comparisons with alternatives, but the description provides enough context for typical usage.

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?

The description adds that the annuity is 'ordinary' and clarifies the rate format, complementing annotations (readOnlyHint, idempotentHint). It does not contradict annotations, but doesn't disclose additional behavioral traits beyond basic definition.

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 extremely concise: two sentences, no fluff. Information is front-loaded with the main purpose, then parameter clarification.

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 financial calculation tool with full schema documentation and an output schema, the description sufficiently covers all necessary context. No gaps are apparent.

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 100%, and the description only reiterates that rate is per-period in percent, which is already in the schema. No additional meaning is provided 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 clearly states it computes the future value of an ordinary annuity, aligning with the tool name 'annuity-fv'. It distinguishes from sibling tools like 'annuity-pv' and 'annuity-payment' by specifying the type of annuity and the return value.

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 does not provide any guidance on when to use this tool over alternatives (e.g., future-value for lump sums, annuity-pv for present value). No when-not or alternative scenarios are mentioned.

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 provide readOnlyHint=true and idempotentHint=true, indicating no side effects and deterministic output. The description adds that it implements the standard annuity formula, but doesn't disclose additional behavioral details like payment timing (end vs beginning of period).

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 sentence of 14 words, concise and front-loaded with the core purpose. Every word earns its place, with a parenthetical reference to the well-known formula name.

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 presence of an output schema, the description need not cover return values. It adequately explains the tool's function for a standard financial formula. Minor omission: it doesn't specify whether payments are ordinary or due, but this is typical for such a 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 coverage is 100%, so the baseline is 3. The description restates that rate is per period, which is already in the schema. It does not add new meaning beyond what the schema provides.

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 computes the level payment amortizing a present value over n periods, also known as the loan-payment formula. This specific verb+resource distinguishes it from siblings like 'annuity-pv' and 'annuity-fv'.

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 indicates that the rate is per period, which guides usage. It implies the tool is for periodic loan or annuity payments. While it doesn't explicitly state when not to use this tool, the context of sibling tools makes the application clear.

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 declare read-only and idempotent behavior. The description adds that the rate is per-period in percent and payments are at period end, providing useful context beyond annotations. 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?

Two concise sentences with no fluff. The key information (ordinary annuity, end-of-period, rate percentage) is front-loaded and efficiently conveyed.

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 financial calculation with complete schema, annotations, and an output schema, the description is sufficient. It could explicitly state the result is PV at time 0, but is otherwise 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. The description's mention of 'level payment at each period end' adds slight context for payment timing, but repeats schema's rate definition. Minimal added value.

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 computes the present value of an ordinary annuity with level payments at period ends. This distinguishes it from sibling tools like annuity-fv (future value) and present-value (general PV).

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 specifies an ordinary annuity with end-of-period payments, but does not explicitly guide when to use this tool over alternatives like annuity-due or other PV calculators. No when-to-use or when-not-to-use advice is given.

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 declare readOnlyHint=true and idempotentHint=true, indicating a safe, deterministic calculation. The description adds context by explaining the calculation logic: payment based on amortization period and balloon due after term. This goes beyond annotations, though it could be more explicit about output format.

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, efficient sentence that conveys the essential purpose without any extraneous words. Every part is meaningful.

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 presence of an output schema (not shown but stated), the description adequately explains the tool's purpose. It lacks details on prerequisites or edge cases but is sufficient for a straightforward financial calculation 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 coverage is 100% with clear parameter descriptions. The description reinforces the relationship between amortMonths and balloonMonths but adds little new semantic value beyond the schema. 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 clearly states the tool computes a balloon loan payment and the remaining balance after the balloon term. It uses specific terms like 'long amortization' and 'shorter balloon term', distinguishing it from sibling tools like 'amortization' or 'interest-only-payment'.

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 it is used for balloon loan calculations but provides no explicit guidance on when to use this versus other similar tools (e.g., amortization, interest-only-payment). No when-not-to-use or alternatives are mentioned.

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 readOnlyHint and idempotentHint, meaning the tool is safe and idempotent. The description adds value by explaining the specific FIRE calculation logic (part-time income offset), but does not contradict 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 a single, well-structured sentence that conveys the essential purpose and calculation logic with zero 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 calculator tool with an output schema (not shown but implied), the description sufficiently explains the purpose and formula. It is complete enough for an agent to understand when and how to use this 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 covers all parameters with descriptions. The tool description adds context by explaining how parameters relate in the Barista FIRE formula (part-time income reduces the amount the portfolio needs to fund). This provides meaning 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 clearly states what the tool computes: the nest egg needed for Barista FIRE, where part-time income covers part of spending, and portfolio funds the remainder at safe withdrawal rate. This distinguishes it from other FIRE-related sibling tools like fire-number and coast-fire.

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 usage for Barista FIRE calculation, which is clear from the name and context. However, it does not explicitly state when not to use this tool or provide alternative sibling tools for comparison.

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 declare readOnlyHint=true and idempotentHint=true. The description adds 'Returns the biweekly payment and the months and interest saved,' which aligns with read-only behavior but provides no additional context about side effects, auth needs, or rate limits. 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 a single, concise sentence that front-loads the purpose and outputs. No superfluous words; every part earns its place.

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 rich annotations, full schema coverage, and presence of an output schema, the description is complete. It explains the key return values (payment, months/interest saved) without needing to reiterate the output schema.

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?

All three parameters (amount, ratePct, termMonths) are fully described in the input schema. The description does not add further meaning beyond the schema, meeting the baseline. The context of 'paying half the monthly payment' is helpful but not parameter-specific.

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: 'Biweekly mortgage acceleration: paying half the monthly payment every two weeks. Returns the biweekly payment and the months and interest saved.' It uses specific verbs and identifies the resource (biweekly mortgage payoff) and its outputs, distinguishing it from sibling tools like amortization or loan-payoff.

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 implicitly indicates usage for biweekly mortgage calculations but does not explicitly state when to use this tool versus alternatives like amortization or loan-payoff. No exclusions or alternative recommendations are provided.

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 confirm readOnly and idempotent behavior. The description adds that volatility and rates are in percent and that dividend yield is optional, which is useful. However, it does not disclose model assumptions (e.g., no early exercise, continuous dividends) beyond what is implied by 'European'.

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 only two sentences (22 words), front-loaded with the core purpose, and contains no redundant or extraneous information. Every word contributes to understanding.

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 moderate complexity (7 parameters, output includes d1/d2, many sibling tools), the description is somewhat incomplete. It lacks guidance on when to use it over alternatives, does not explain limitations (e.g., no American options), and does not mention the output schema (though context indicates one exists).

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?

Input schema has 100% coverage with descriptions for all 7 parameters. The description reiterates that volatility/rates are in percent (already clear from parameter names) and highlights the optional dividend yield. This adds minimal value beyond the schema, so the baseline score 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 clearly states the tool computes the Black-Scholes price of a European call or put option, and explicitly mentions it also provides d1/d2. This differentiates it from sibling tools like 'option-greeks' or 'intrinsic-time-value'.

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 use for European options but does not explicitly guide when to use this tool versus alternatives such as 'option-greeks' or 'put-call-parity'. It lacks direct comparisons or exclusions, leaving the agent to infer context.

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 declare readOnlyHint=true and idempotentHint=true, so the description's statement of computing Macaulay and modified duration is consistent. No additional behavioral traits (e.g., assumptions about yield curve or reinvestment) are disclosed beyond 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 a single sentence that is concise and to the point. However, it could be improved by structuring the two metrics separately for easier parsing.

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 that an output schema exists, the description does not need to explain return values. However, it omits typical usage caveats (e.g., assumptions of flat yield curve, reinvestment at yield), leaving some gaps for a finance 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 coverage is 100%, so parameters are documented in the input schema. The description adds no extra meaning beyond what the schema provides, so baseline score of 3 applies.

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 Macaulay duration (PV-weighted average time of cashflows in years) and modified duration (price sensitivity to yield). It distinguishes itself from sibling tools like bond-price and yield-to-maturity by specifying the duration metrics.

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 provided on when to use this tool versus alternatives like convexity or yield-to-maturity. The description only defines what it computes without suggesting usage context.

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 provide readOnlyHint and idempotentHint. Description adds standard bond pricing formula but no additional behavioral traits beyond what annotations cover.

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?

Single sentence that front-loads the key information: the tool's purpose and the formula. 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?

Given the presence of an output schema and clear annotations, the description is sufficient for a simple calculator. Could optionally mention default coupon frequency but not required.

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 does not add extra meaning beyond parameter names and schema descriptions. It mentions the formula but doesn't elaborate on how parameters are used.

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 the tool calculates the price of a coupon bond as present value of coupons plus face value. Distinguishes from siblings like zero-coupon-price and yield-to-maturity.

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 on when to use this tool versus alternatives like bond-duration or yield-to-maturity. With many bond-related siblings, explicit usage context is missing.

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 declare readOnlyHint=true and idempotentHint=true, so the safety profile is clear. The description adds the formula but does not disclose additional behavioral traits. No contradiction with 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 a single sentence that is concise and front-loaded with purpose. It could be slightly more structured but is efficient.

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 simple tool with 3 parameters and an output schema, the description is complete. It provides the formula and output components, leaving no gaps for the agent.

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 for parameters are basic. The description adds meaning by showing how parameters relate in the formula (fixedCosts / (pricePerUnit - variableCostPerUnit)), which helps the agent understand usage.

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 break-even volume using the formula 'fixed costs divided by the per-unit contribution (price - variable cost), plus the revenue at that volume.' It specifies the resource and verb, and is distinct from sibling tools like 'contribution-margin' or 'cagr'.

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 usage by stating the formula, but does not explicitly say when to use this tool or how it compares to siblings. No exclusions or prerequisites are provided.

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 declare readOnlyHint=true and idempotentHint=true, indicating safe, deterministic behavior. The description adds that it splits income into three categories, but does not elaborate on output format, limits, or edge cases. Since annotations cover safety, a score of 3 is appropriate for minimal added context.

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 concise sentence with no redundancy. It efficiently conveys the core purpose without 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?

The tool is simple with one parameter and has an output schema (not shown). The description mentions the split categories but does not specify that the output will contain amounts for each category, nor does it confirm the exact percentages (though implied by the name). Missing guidance on usage and output format detracts from completeness.

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 the parameter 'monthlyIncome' described as 'Monthly take-home income.' The description does not add additional meaning beyond the schema, so baseline score of 3 applies.

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 performs a 50/30/20 budget split of monthly income into needs, wants, and savings. The verb 'split' and resource 'budget' are specific, and it distinguishes itself from sibling tools which are mostly financial calculators unrelated to budget allocation.

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 on when to use this tool versus alternatives. There is no mention of prerequisites, ideal use cases, or situations where this tool should not be used. The description simply states what it does without contextual advice.

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 declare readOnlyHint=true and idempotentHint=true, but the description adds value by clarifying the output is a decimal representing a rate (e.g., 0.07 = 7%). No contradictions, but could mention that it assumes compounding over equal periods.

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 extraneous details. The first sentence immediately states the purpose, and the second clarifies the output format. Efficient and well-structured.

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 simple nature of the tool, complete schema, output schema, and clear annotations, the description is largely adequate. Minor gap: no mention of handling zero or negative years, but not critical for standard use.

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 descriptions cover all three parameters (begin, end, years) with clear names. Description does not add additional semantic information beyond the schema, so 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 computes compound annual growth rate between two values over years, specifying the output format (decimal). This distinguishes it from siblings like 'percentage-change' or 'future-value' which serve different purposes.

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 explicit guidance on when to use CAGR versus alternatives such as 'percentage-change' or 'irr'. No mention of prerequisites, edge cases, or situations to avoid. The description only states what it does, not when 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?

Annotations already declare the tool as read-only and idempotent, indicating safe behavior. The description adds the formula context but does not disclose potential edge cases (e.g., handling of non-annual periods) or output format.

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, efficient sentence with no wasted words. It is front-loaded with the key term 'capitalization rate'.

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 financial calculation tool with two numeric inputs and an output schema, the description is adequate. It does not explain the return value, but the output schema presumably covers that. The tool is straightforward.

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 basic descriptions. The description adds meaning by explaining the formula (NOI as percent of property value), which goes beyond the parameter names and schema 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 'Capitalization rate: net operating income as a percent of property value' clearly states the tool's purpose: calculating a cap rate. It uses a specific verb ('calculate' implied) and resource (cap rate from NOI and property value). Among the sibling tools, none are directly similar, so it stands out.

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 implied usage (when cap rate is needed) but gives no explicit guidance on when to use or avoid this tool versus alternatives. No exclusions or alternative tool names are mentioned.

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 declare readOnlyHint=true and idempotentHint=true, so the description does not need to restate safety. It adds minimal behavioral context beyond the calculation formula. No contradictions with 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?

Single sentence of 15 words, no redundancy. Every word earns its place by stating the metric and its calculation. Excellent economy.

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 calculator with an output schema (as per context), the description is fully adequate. It explains the result format (percent) and the input relationship. No additional detail is necessary.

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 clear parameter descriptions. The tool description integrates both parameters into the formula (annual cash flow / cash invested), adding meaning beyond the schema by showing how they relate. This compensates for the schema's brief 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?

Description clearly states the tool computes cash-on-cash return as a percentage. It specifies the formula (annual pre-tax cash flow / cash invested), making the purpose unambiguous and well-differentiated from sibling tools like cap-rate or roi.

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 explicit guidance on when to use this tool over siblings. The description implies use for real estate investment analysis, but lacks when-not-to-use or alternative tools. Given many similar financial ratios in siblings, some usage context would improve scoring.

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?

The description discloses return values and core logic, aligning with readOnlyHint and idempotentHint annotations. It adds context beyond annotations by naming the specific outputs, but does not detail behavior for edge cases (e.g., rounding) or default assumptions (e.g., withdrawal rate default).

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 concise sentence that effectively front-loads the tool's purpose and outputs. Every word adds value with no redundancy.

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 presence of an output schema and full parameter documentation, the description provides adequate context. It explains the core logic and lists return fields, though it could clarify the meaning of 'coasts' or the default withdrawal rate (already in schema). Minor gap in standalone completeness.

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 clear parameter descriptions. The description does not add significant meaning beyond the schema—it references 'current nest egg' and 'FIRE target' but does not elaborate on parameter format, constraints, or interactions. 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 evaluates Coast FIRE: whether the current nest egg grows untouched to reach the FIRE target. It specifies the return fields (target, projected balance, coast status, shortfall), making the purpose unambiguous and distinct from siblings like 'fire-number' or 'portfolio-longevity'.

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 implicitly indicates when to use (to check Coast FIRE status) but provides no explicit guidance on when not to use or how it differs from alternatives. No mention of prerequisites or exclusion criteria, which is a moderate gap.

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?

Adds important behavioral detail: contributions are 'paid at period end'. Annotations already indicate readOnlyHint and idempotentHint, which are consistent with a calculation tool. 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?

Two sentences, no extraneous words. Front-loaded with core purpose, then clarifying generalization. Efficient and effective.

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 presence of an output schema and the tool's mathematical nature, the description fully covers what an agent needs to invoke it correctly. No gaps.

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 covers 100% of parameters with descriptions. The description adds semantic value by linking periodsPerYear to sibling tools, enhancing understanding beyond basic parameter documentation.

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 'compound growth at any frequency' with optional contributions, and explicitly distinguishes itself from siblings like future-value and contributions by noting it generalizes them.

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 indirectly guides usage by mentioning parameter values that correspond to specific siblings (periodsPerYear=1 for future-value, periodsPerYear=12 for contributions), but does not explicitly state when to prefer this tool over others.

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 behavior. Description adds minimal behavioral context, just confirming the computation.

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?

Single sentence concisely conveys purpose, front-loading key information with 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?

Given simplicity, output schema exists, and annotations are provided, description is sufficient but could slightly expand on inputs or assumptions.

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 provides full descriptions for both parameters. Tool description adds no additional meaning; baseline score for high coverage.

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 explicitly states it computes 'Contribution margin per unit and as a percent of price,' clearly defining the output and differentiating it from sibling tools like 'margin-markup'.

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 on when to use this tool versus alternatives; simply states what it does without context or 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating a safe calculation. Description adds the key behavioral trait of optional step-up per year, which is not captured by 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?

Single sentence, front-loaded with core purpose, no wasted words. Efficiently communicates the essential function.

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 output schema exists, description need not explain returns. Tool is simple with well-documented parameters, but missing usage guidance for selection among 43 sibling tools reduces completeness.

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 100%, so the baseline is 3. Description adds minimal extra meaning beyond the schema, only clarifying that the contribution is fixed and step-up is annual.

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 the future value of a fixed monthly contribution, optionally stepping up each year. This distinguishes it from sibling tools like 'future-value' (lump sum) and 'annuity-fv' (periodic payments).

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 explicit guidance on when to use this tool versus alternatives like 'annuity-fv' or 'compound-interest'. Usage is implied but not clarified, and no exclusions are mentioned.

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?

The annotations already indicate read-only and idempotent behavior. The description adds the unit 'years^2' and the relationship to duration, which provides some behavioral context beyond the annotations. However, it does not disclose additional behavioral traits like precision or assumptions (e.g., clean price vs dirty price).

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 sentence that efficiently conveys the core concept and relationship to duration. It front-loads the key information and has no superfluous content, though a bit more detail on usage could be added without harming structure.

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 presence of an output schema (not shown) and full parameter descriptions, the description is complete enough for a well-understood financial metric. It explains the purpose and relationship to duration, which suffices for an agent to invoke it correctly alongside sibling tools.

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% description coverage for all 5 parameters, so the schema already provides their meaning. The description adds no further semantic details about the parameters, remaining at the baseline score.

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 computes bond convexity, defined as the curvature of price with respect to yield. The verb is implicit (compute) and the resource is the convexity measure. This directly distinguishes it from the sibling tool 'bond-duration' which is a first-order measure.

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 mentions 'used alongside duration', which provides clear context for when to use this tool relative to the sibling 'bond-duration'. However, it lacks explicit when-not-to-use or alternative scenarios, though the context is sufficient for a specialized financial metric.

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 readOnlyHint=true and idempotentHint=true, so the tool is safe and idempotent. Description adds the important behavioral detail of returning null when payment can't cover first month's interest.

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, front-loaded with purpose. No unnecessary words. Efficient and clear.

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 that an output schema exists and annotations cover safety, the description is complete. It explains the core function and the edge case (null). No missing information for agent to select and invoke 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?

Schema coverage is 100% with descriptions for all parameters. The description adds context about fixed monthly payment and the null condition, which supplements the schema but doesn't significantly enhance understanding beyond 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?

Description clearly states it calculates months to clear balance and interest paid, with specific condition for null. Distinguishes from siblings like 'debt-payoff' by being credit-card specific.

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 explicit guidance on when to use this tool versus alternatives like 'loan-payoff' or 'debt-payoff'. The only usage clue is the null condition for insufficient payment.

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 declare readOnlyHint=true and idempotentHint=true, indicating a pure read operation. The description adds no behavioral context beyond the formula, so it provides minimal additional transparency.

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 extremely concise, using only one sentence. It is front-loaded but lacks minor elaborations that could be included without verbosity.

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 the presence of an output schema, the description is minimally complete. However, it does not explain the return value or any constraints beyond the formula.

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 100%, with each parameter already described. The description adds no extra meaning beyond what the schema 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 the formula: current assets over current liabilities. It specifies the exact resource and operation, distinguishing it from sibling tools like 'quick-ratio'.

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 explicit guidance on when to use this tool versus alternatives. The context of siblings includes other ratios, but the description does not provide when-to-use or when-not-to-use information.

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 readOnlyHint and idempotentHint, so the tool is safe and deterministic. The description does not add behavioral details beyond the formula; 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?

One concise sentence that efficiently conveys the tool's purpose. No redundant or 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?

For a simple calculation, the description is adequate. Output schema likely covers return values. However, it could mention that it assumes a standard bond without accrual adjustments.

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 clear parameter descriptions. The description adds minimal extra meaning, simply restating the formula involving price and coupon rate. Face value role is slightly implicit.

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 the tool computes current yield, defined as annual coupon divided by current price. This distinguishes it from siblings like yield-to-maturity or accrued-interest, which involve more complex calculations.

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 explicit guidance on when to use this tool versus alternatives. While the sibling list includes similar tools (e.g., yield-to-maturity), the description does not differentiate conditions for use.

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 indicate readOnly and idempotent. Description adds specific tax rates (25%, Soli 5.5%, church tax reduction formula) and confirms no Freigrenze for capital income, providing behavioral context beyond 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?

Description is a single dense sentence that efficiently conveys key information. Front-loads purpose but could be split for readability; no unnecessary 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?

Given the tool's complexity (multi-year, multiple tax components), the description covers essential aspects: years, allowance, rates, soli, church tax. Output schema exists to detail return values, so completeness is high.

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 each parameter. The description adds overall context (e.g., Sparerpauschbetrag built in, church tax formula) but does not significantly enhance individual parameter meaning 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?

Description clearly identifies the tool as calculating German capital gains tax (Abgeltungsteuer) for specific tax years, with built-in allowance and rates. It distinguishes itself from sibling financial calculators by focusing on a specific German tax.

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 usage for computing capital gains tax in Germany for years 2023-2026 but does not explicitly state when to use this tool over alternatives or provide 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?

Annotations already indicate read-only and idempotent behavior. The description adds that it flags insolvent budgets and returns payoff order, total interest, and months, providing behavioral context beyond the annotations without contradicting them.

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 cover purpose, constraints, method options, and outputs. Every sentence adds essential information without redundancy. Front-loaded with key action and context.

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 description, combined with the complete input schema and presence of an output schema (as indicated), provides sufficient information for an agent to understand inputs, outputs, and key behaviors like insolvency detection. No critical gaps remain.

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?

With 100% schema coverage, the baseline is 3. The description enhances understanding by explaining the rationale behind the two methods (minimizes interest vs. clears soonest) and reinforces that monthlyBudget is fixed, adding value beyond the schema definitions.

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 creates a multi-debt payoff plan under a fixed monthly budget, explicitly details two methods (avalanche and snowball) with their effects, and lists return values. It distinguishes itself from sibling tools like 'credit-card-payoff' or 'loan-payoff' by focusing on multiple debts and a fixed budget.

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 usage context (multiple debts, fixed monthly budget) but does not explicitly state when not to use it or recommend alternatives. It provides clear guidance on method choice, which aids selection among the two variants.

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 declare readOnlyHint and idempotentHint, so the tool is safe and idempotent. The description adds value by explaining the formula: 'a fixed percent of the reducing book value,' which clarifies the calculation method beyond what annotations provide.

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: one explains the method, one states outputs. It is front-loaded and contains no filler. Could be slightly more structured, but overall efficient.

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 3-parameter tool with existing output schema, the description adequately covers the calculation and return values. It does not address nuances like salvage value, but such details may be in the output schema.

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 parameters are documented. The description adds meaning by stating year is 1-based and that the rate is applied to the declining balance, which is not explicit in the schema alone. It also sets expectations for returned values.

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 computes declining-balance depreciation for a given year, returning depreciation and remaining book value. It uses a specific verb ('Returns') and distinguishes the method from siblings like straight-line or double-declining.

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 like straight-line or sum-of-years-digits. It lacks explicit context about appropriate scenarios or prerequisites.

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 declare readOnlyHint and idempotentHint true, meaning no side effects and deterministic output. The description adds that the tool does not contain tax tables, which is a behavioral trait beyond the annotations. 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?

Three sentences that are front-loaded and concise. Every sentence adds essential information: purpose, key design constraint (no tax tables), data types for inputs, and unit consistency reminder. No fluff.

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 10 parameters and no output schema shown, the description explains relationships (e.g., church tax percent of income tax, contribution ceilings) and unit consistency. It does not explain the calculation algorithm or edge cases, but the explicit mention of manual figures and required inputs makes it adequately complete for agent 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?

Schema coverage is 100%, so each parameter has a description. The description adds overarching context: distinguishes between amount inputs (incomeTax, soli) and percentage inputs (churchTaxPct, social rates) and explains the role of contribution ceilings. This adds value beyond individual parameter 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 the tool converts German gross salary to net salary (Netto from Brutto). The title includes '(manual figures)' and the description explicitly says 'No tax tables are baked in', distinguishing it from sibling tools like 'de-net-salary' which likely automates tax lookup.

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 tells the agent to look up current year's statutory figures and pass them in, and to use consistent units (e.g., all annual). It implies when not to use this tool (when tax tables are available). Explicit alternatives are not named, but the manual nature provides clear 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 indicate readOnly and idempotent. Description adds behavioral context: the amount is uniform since 2023 and provides monthly/annual totals. It does not detail return format or limitations, but transparent enough for the low-complexity tool.

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?

Single sentence, concise and front-loaded with key information (what, when, how). 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?

Given low complexity (2 params), presence of output schema, and description explaining return values (monthly/annual totals), it is complete. No gaps identified.

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 covers 100% of parameters (year, children). Description implies year and children but does not add meaning beyond schema. Baseline 3 is appropriate as schema already documents parameters.

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 computes German child benefit (Kindergeld) for a given year (2023-2026) as flat monthly and annual totals per child. It uses specific verb 'compute' (implied) and resource 'Kindergeld', distinguishing it from sibling financial calculators.

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 does not explicitly state when to use this tool or provide alternatives. It is implied for German child benefit queries, but no guidance on when not to use it or comparative context with siblings.

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 declare readOnlyHint=true and idempotentHint=true, so the tool is safe and non-destructive. The description adds that it 'classifies' and 'computes' contributions, which aligns with these hints and provides additional detail on the computation logic (e.g., factor F, thresholds). 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 a single, dense sentence that packs in the purpose, legal reference, year range, and two key outputs. It is front-loaded with the tool's name and core function. While it could be broken into multiple sentences for readability, it remains efficient and informative.

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 (7 parameters, specific German social insurance rules, and an output schema), the description covers essential aspects: classification, contribution basis computation, and split. It mentions the year thresholds and factor F, which are crucial for understanding the tool's behavior. The output schema exists to detail return values, so no further explanation needed.

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 100%, so baseline is 3. However, the description adds value by explaining the overall computation context (e.g., 'Faktor F from the year's rates') and mentions age-related rules ('under 23 skips the childless care surcharge'), which goes beyond schema descriptions. Thus, a 4 is justified.

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 classifies monthly pay, computes reduced contribution bases, and employee/employer split for German Midijob, specifying the legal paragraph and year range. This is highly specific and distinguishes it from sibling tools which are general financial calculators.

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 use when dealing with German Midijob contributions for 2023-2026, but does not explicitly state when not to use or list alternatives. However, the niche nature of the tool and clear problem statement make its usage context clear, so a 4 is appropriate.

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 indicate readOnlyHint and idempotentHint, and the description adds rich behavioral context: it explains income tax and Soli use the official BMF Programmablaufplan, church tax from PAP base, and social insurance using yearly ceilings and rates. It notes the 2024 retroactive December tariff and default KV Zusatzbeitrag, going well beyond 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 a single coherent paragraph that front-loads the core purpose and then adds necessary details. It is efficient with no wasted words, though slightly dense. It earns its place by being informative without being overly verbose.

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, nested objects, output schema), the description is remarkably complete. It covers year range, calculation sources, default behaviors, exceptions, and sibling tool reference. The high schema coverage and presence of output schema complement the description, making it fully adequate for correct agent selection and 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?

Input schema has 91% description coverage, already detailing most parameters. The description adds valuable context beyond schema, e.g., explaining the 'Faktor' parameter for married couples and clarifying that 'kvZusatzPct' defaults to the official average. While not individually documenting every parameter, it provides useful overarching semantics.

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 computes 'Exact German net (Netto) salary from annual gross (Brutto) for tax years 2023-2026', providing a specific verb+resource+scope. It also distinguishes from the sibling 'de-gross-to-net' by noting earlier years are rejected and directing users to that alternative.

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 (tax years 2023-2026) and when not to (earlier years), with a clear alternative: 'use de-gross-to-net with self-supplied figures instead'. It also details defaults and optional parameters like kvZusatzPct defaulting to the year's average.

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 readOnly and idempotent behavior. The description adds some compounding detail but does not clarify the specific formula or how it differs from other depreciation methods, especially given the 'up' parameter for appreciation.

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, no redundant information. Fairly concise, though the first sentence could be clearer about the compounding mechanism.

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 existence of multiple depreciation siblings and an output schema, the description does not explain the specific depreciation method or how it fits with other tools. It leaves the agent without enough context to distinguish use cases.

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 descriptions cover all parameters at 100%. The description adds context about yearly compounding but does not provide substantial additional meaning 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 clearly states that the tool computes a value after compounding down or up at a yearly percentage rate over years, specifying it's used for long-term assets. However, it does not differentiate from sibling depreciation tools like straight-line or declining-balance, which could cause confusion.

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 provided on when to use this tool versus alternatives like straight-line-depreciation or compound-interest. The description lacks context for selection.

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 declare readOnlyHint and idempotentHint, indicating no side effects. The description adds a behavioral constraint ('capped at the contribution ceiling') but does not elaborate on return format, error conditions, or authorization needs. With annotations covering safety, the description provides adequate but not rich context.

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 sentence that packs necessary information efficiently. It is front-loaded with the tool name and legal reference, but the dense structure may be slightly hard to parse. Still, it is concise with 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?

Given the full schema descriptions and the presence of an output schema, the description covers the main inputs and calculation context. It does not explain return values, but the output schema handles that. The description is sufficiently complete for a read-only calculator 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 coverage is 100% with descriptions for all 4 parameters. The description adds meaning beyond the schema by explaining how parameters are used (e.g., Durchschnittsentgelt, cap, Rentenwert halves, optional monthly pension projection). This compensates for the baseline of 3.

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 tool as a calculator for German pension points, specifying the legal basis (paragraph 63 SGB VI), the years covered (2023-2026), and the key inputs (annual gross, contribution ceiling, Rentenwert). This sets it apart from sibling financial calculators.

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 explicit guidance on when to use this tool versus alternatives (e.g., other German-specific tools like de-net-salary). It implies usage for pension point calculation but does not state when not to use or mention alternative tools.

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 declare readOnlyHint=true and idempotentHint=true, indicating safe, idempotent calculation. The description adds that it computes 'amount off and the final price', which is consistent but provides only marginal additional behavioral context beyond 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?

Single sentence of 12 words, front-loaded with purpose ('A single percentage discount'). Every word earns its place with no redundancy.

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 output schema exists (not shown but indicated), the description need not explain return values. The tool is simple with two well-documented parameters and annotations covering safety. Description is sufficient for a straightforward calculation 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?

Input schema covers both parameters with descriptions ('Original price.', 'Discount in percent.'). The description hints at outputs but does not add new meaning to parameters. With 100% schema coverage, 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?

Description clearly specifies a single percentage discount tool that calculates amount off and final price, distinguishing it from sibling tools like 'successive-discounts' (multiple discounts) and 'percentage-change' (relative change).

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 explicit guidance on when to use this vs alternatives like 'successive-discounts' or 'percentage-change'. The phrase 'single percentage discount' implies a single discount scenario but does not provide clear when-not-to-use or alternative tool names.

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 declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false, which the description does not contradict. The description adds behavioral context by explaining the discounting mechanism. It does not elaborate on return format or assumptions, but for a simple calculation tool, this is sufficient.

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 sentence that is concise and front-loaded, delivering the core purpose and key differentiation without extraneous content.

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 low complexity, presence of annotations, and full schema coverage, the description is complete. It covers the essential concept and distinguishes from a sibling tool, requiring no additional context for proper use.

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 each parameter described. The tool description does not add new meaning beyond the schema; it only mentions 'per-period rate' which matches the schema description for ratePct. Baseline 3 is appropriate as no extra value is provided.

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 explicitly states it computes the discounted payback period, comparing it to the sibling tool 'payback-period' and clarifying that cashflows are discounted at the per-period rate. This clearly specifies the verb and resource, distinguishing it from related tools.

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 implicitly guides usage by positioning it as a variant of payback-period with discounting, but does not explicitly state when to use this over other alternatives like NPV or IRR. The context is clear but lacks explicit when-not or alternative 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 declare readOnlyHint=true and idempotentHint=true, so the agent knows it's a safe read. The description adds context: it returns 'units accumulated, total invested, average cost, and final value at the last price', clarifying what the agent can expect.

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 two sentences, front-loaded with the core operation and immediately followed by output details. No wasted words or redundancy.

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 is simple with two parameters and an output schema exists (signaled by 'Has output schema: true'), so the description need not detail returns. It still lists them, providing a complete picture. No gaps.

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 clear parameter descriptions ('Price at each purchase period', 'Fixed amount invested each period'). The description briefly restates these ('buying a fixed amount each period at the given prices') but adds no new meaning 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 clearly states the tool computes dollar-cost averaging: 'buying a fixed amount each period at the given prices' and lists the specific outputs (units, total invested, average cost, final value). It distinguishes from sibling tools like compound-interest or future-value by focusing on a unique strategy.

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 for calculating DCA results but gives no explicit guidance on when to use it vs. alternatives (e.g., lump-sum comparison). No exclusions or best-use scenarios are mentioned.

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 readOnly and idempotent hints. The description adds the behavioral constraint that the calculation does not fall below salvage value, which is valuable beyond 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 extremely concise, fitting in a single phrase. It front-loads the method name and formula with no redundant words. Slightly informal but effective.

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 financial calculator with a clear formula and output schema, the description covers the essential behavior. Could mention return value format or edge cases, but 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 description coverage is 100%, so the baseline is 3. The description does not add extra semantic meaning to parameters; it only restates the overall formula.

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 explicitly states the depreciation method and formula: 'Double-declining-balance depreciation: 2/usefulYears of the book value each year, not falling below salvage.' It clearly distinguishes from sibling tools like straight-line or units-of-production depreciation.

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 offers no guidance on when to use this method over alternatives, nor does it mention any context or prerequisites. Usage must be inferred from the formula alone.

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?

The description adds the formula DSCR = NOI / annual debt service, which is behavioral context beyond the annotations (readOnlyHint, idempotentHint). No contradictions, and the formula clarifies the calculation.

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, self-contained sentence that states the formula without any extraneous words. It is front-loaded and concise.

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 output schema exists and the tool is a simple calculation, the description covers the essential behavior. It does not discuss edge cases or assumptions, but the minimal description is adequate for this straightforward metric.

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 described. The tool description repeats the formula but adds no new meaning beyond what the schema already provides, so baseline score 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 explicitly defines the debt service coverage ratio as net operating income divided by annual debt service, clearly identifying both the verb (calculates) and the resource (DSCR). It distinguishes itself from sibling financial ratio tools like cap-rate and cash-on-cash by focusing on debt coverage.

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 usage for assessing debt coverage but provides no explicit guidance on when to use this versus alternatives, nor any exclusions or prerequisites. Sibling tools cover many financial ratios, so more context would help.

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 declare readOnlyHint=true, idempotentHint=true, so the description doesn't need to repeat that. It adds the formula but does not disclose edge cases (e.g., zero income) or rounding behavior. Given annotations, the description is adequate but not exceptional.

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, clear sentence with no redundancy. All words are meaningful, and the purpose is immediately obvious.

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 (two numeric inputs, straightforward calculation), the description provides enough context. However, it could mention handling of zero income or output format (e.g., percent value). Still, it is mostly 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% with clear parameter descriptions. The description adds the formula context, which clarifies how the parameters are used together. This adds value beyond the schema alone.

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 computes the debt-to-income ratio as a percentage using the formula monthly debt divided by gross monthly income. The name and title match exactly, and there is no confusion with sibling tools.

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 provided on when to use this tool versus alternatives. Among siblings, there are many financial ratio calculators (e.g., dscr, cap-rate), but the description does not help the agent differentiate or decide when to select dti.

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 declare readOnlyHint and idempotentHint, covering safety. The description adds behavioral context by specifying the conversion direction and the role of toNominal flag. 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?

A single well-structured sentence that front-loads the main purpose and concisely covers both conversion directions. No redundant or 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?

For a simple mathematical conversion tool with complete schema and existing output schema, the description is adequate. It covers the core functionality and directionality. Minor gap: no mention of edge cases or output format, but output schema likely handles that.

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 clear parameter descriptions. The tool description adds a high-level overview but does not provide extra details beyond the schema. Baseline of 3 is appropriate as the schema already carries the semantic load.

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 converts between nominal and effective annual rates (APY) for a given compounding frequency, and mentions the toNominal flag for reverse conversion. This is a specific verb-resource pair that distinguishes it from siblings which are all different financial calculators.

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 explains what the tool does but does not provide explicit when-to-use or when-not-to-use guidance. It doesn't discuss alternatives or prerequisites, though the tool's function is sufficiently unique among siblings that lack of exclusion criteria is acceptable.

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 declare readOnlyHint=true and idempotentHint=true. The description adds no extra behavioral context beyond the formula, so it meets the baseline with 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?

Single sentence, front-loaded with the key concept 'Months of runway', 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?

Given the simplicity of the tool and presence of annotations and output schema, the description is nearly complete. It could mention the return value unit, but not critical.

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 the description merely restates the relationship ('divided by') without adding meaning beyond what the schema already provides.

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 the tool calculates months of runway via division, which is a specific resource and operation. However, it could explicitly use a verb like 'calculate' to be clearer.

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 on when to use this tool vs alternatives like 'savings-rate' or 'fire-number'. No exclusions or context provided.

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 indicate readOnlyHint and idempotentHint, which the description does not contradict. It adds context by describing the output (compounded balances and amount lost), beyond what annotations provide, covering behavioral traits of the calculation.

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?

Single sentence that is front-loaded with the purpose. No unnecessary words; every part earns its place.

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 with an output schema, the description explains the effect and outputs. It could mention constraints (e.g., non-negative values) but is reasonably complete given the tool's simplicity.

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 all 4 parameters. The description does not add additional meaning or constraints for parameters beyond what the schema already provides, meeting the baseline for high coverage.

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 computes the effect of an annual fee on compounded balance, showing gross vs net and amount lost. It uses specific verbs and identifies the resource, but does not explicitly distinguish from siblings like 'compound-interest'.

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 on when to use this tool versus alternatives (e.g., 'compound-interest' or 'future-value'). The description lacks context for appropriate use cases or exclusions, leaving the agent to infer.

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 behavior. The description adds context about the calculation (gap, years, default values) and includes 'No advice' disclaimer, providing behavioral clarity beyond 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 efficient sentences that front-load the main purpose and key details (default rate, optional savings/growth) without extraneous text.

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 5 parameters (all documented) and the presence of an output schema, the description adequately explains the tool's outputs (target, gap, years). It is complete for a financial calculator with clear defaults.

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 100% with clear parameter descriptions. The tool description adds overall context about how parameters combine to compute the FIRE number, enhancing understanding beyond individual schema entries.

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 computes the FIRE target nest egg from annual spend and a safe withdrawal rate, plus the gap and years to reach it. It uses specific verbs and resources, distinguishing it from sibling tools like barista-fire and coast-fire.

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 usage for FIRE calculations but offers no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among the many sibling financial calculators.

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 behavior. The description adds the important behavioral detail of annual compounding, which is not captured by annotations. This clarifies the calculation frequency beyond what structured fields provide.

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, concise sentence that delivers the core functionality immediately. No wasted words; it is front-loaded and efficient.

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 numeric parameters, output schema exists), the description is sufficient. It specifies the cash flow type and compounding frequency. Minor missing context like currency assumption is negligible.

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 3 applies. The description does not add meaning beyond the schema's parameter descriptions; 'single lump sum' is a general context note, not parameter-specific. No extra semantics are provided.

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 tool as calculating the future value of a single lump sum compounded annually. It uses a specific verb ('future value') and resource ('single lump sum'), distinguishing it from siblings like 'present-value' (reverse) and 'annuity-fv' (multiple cash flows).

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 usage for single lump sum with annual compounding but provides no explicit guidance on when to use this over alternatives (e.g., 'annuity-fv' for periodic payments). No when-not-to-use or alternative tools are mentioned.

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 behavior. The description adds that the tool relies solely on the caller-supplied rate, which is consistent and provides additional context beyond 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 concise sentences with no wasted words. The core purpose and constraint are 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 tool with two well-documented parameters and an output schema, the description fully covers the behavior, including the critical point that no rate lookup occurs.

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?

Both parameters (rate, amount) have descriptions in the input schema that match the explanation in the tool description. No additional semantic value is added 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 clearly states the tool converts an amount using a user-supplied rate, with no rate lookup. This distinguishes it from sibling tools that involve automatic rate calculations or lookups.

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 indicates the rate must be provided by the caller and no lookup occurs, implying it's for cases where the user already has a rate. However, it does not explicitly mention alternatives or when-not-to-use.

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?

The description restates the calculation but adds no behavioral context beyond annotations. Annotations already declare readOnlyHint and idempotentHint, so the burden is lower.

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 extremely concise with one sentence, front-loading the formula. It loses one point for being overly terse, but is structurally appropriate.

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 presence of an output schema, the description is fully adequate. It provides the essential formula without needing extraneous details.

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 the schema already documents parameters. The description adds no additional meaning beyond the formula, earning the baseline score.

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 the formula 'price divided by gross annual rent' clearly, defining the tool's purpose as a specific real estate metric. It uniquely identifies the tool among many financial 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?

No explicit guidance on when to use this tool versus alternatives. Usage is implied by the formula, but no when-not-to-use or alternative tool comparisons are provided.

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 declare readOnlyHint=true and idempotentHint=true, indicating safe read-only behavior. The description adds the formula context but no additional behavioral traits (e.g., how division by zero is handled, rounding, or period assumptions). It does not contradict 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 a single sentence containing the essential formula. Zero wasted words, perfectly front-loaded. Every part earns its place.

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 an output schema (stated but not shown), so return value documentation is likely handled there. The description explains the calculation formula and result unit (percent). However, it omits edge cases like zero starting value or multi-period handling. For a simple calculation tool, this is nearly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.