calculators

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

No annotations are provided, so the description carries full burden. It does not explicitly state that the tool is read-only or has no side effects, but as a calculator it is implied to be stateless. The description could better disclose any rate limits or permissions, but it is not misleading.

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 with no unnecessary words. It efficiently conveys the tool's purpose and key inputs.

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 complexity of 8 parameters and no output schema, the description is incomplete. It fails to explain the tiered match structure, growth rate, and output format, leaving the agent with insufficient context to use the tool correctly.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, yet the description only explains salary and contribution rate. It omits the remaining 6 parameters (tiers, growth rate, years) which are critical for the match calculation. The description adds minimal 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 it calculates 401(k) employer match, free money, yearly savings, and long-run growth. It uses specific verb 'calculate' and specifies the resource (employer match). No sibling tool has a similar purpose, so it distinguishes well.

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 saying 'enter salary and contribution rate', but does not provide explicit when/when-not guidance or mention alternatives. Since no other 401k match calculator exists among siblings, the lack of exclusions is acceptable but still minimal.

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?

Lacking annotations, the description fails to disclose behavioral traits such as side effects, authorization needs, or that it is a pure computation with no data storage. It only states outputs but not format or whether results are persisted.

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 efficient and front-loaded. No wasted words, clearly communicates the tool's purpose and key inputs/outputs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 8 required parameters and no output schema, the description is too brief. It does not specify the return structure (e.g., numeric values, breakdown), missing essential context for a calculator tool. Sibling differentiation is not addressed beyond the focused topic.

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 0%, so description bears the burden. It names several inputs (task volume, time saved, review effort, API costs) which map to 5 of 8 parameters, but does not explain loadedHourlyCost or automationCoveragePct. Partial compensation for missing 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 clearly states the tool estimates payback of automating a process with AI, with specific inputs and outputs. It distinguishes itself from generic calculators like ai_roi_calculator or break_even_calculator by focusing on AI automation payback with detailed process parameters.

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 siblings like ai_roi_calculator or break_even_calculator. The description does not mention prerequisites, exclusions, or scenarios where this tool is inappropriate.

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

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

No annotations are provided, so the description carries full burden. It describes the tool as a calculator that compares costs, implying it is read-only and non-destructive. However, it does not explicitly state side effects, such as whether data is persisted or any authorization needed. For a calculator, this is adequate but minimal.

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 long, front-loaded with the tool's purpose, and contains no filler. Every word adds value.

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 has 3 required parameters and no output schema, the description explains what it computes (break-even token volume) and the comparison outcome. However, it does not specify the return format or whether it's a simple text output, which may leave an agent uncertain about the result structure. Adequate but not fully 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 description coverage is 0%, meaning the description adds no information about individual parameters. The description mentions 'API price', 'self-host fixed cost', and 'token volume' in a generic way, but does not clarify units, ranges, or distinctions like 'apiPricePerMtok' being per million tokens. Parameter names are somewhat self-explanatory, but the description should have compensated for the lack of 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 clearly states the tool compares monthly cost of hosted LLM API vs self-hosting GPUs, and finds break-even token volume. It uses specific verb 'Compare' and distinguishes from sibling calculators (e.g., not a generic ROI calculator).

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 cost comparison but does not provide explicit guidance on when to use versus alternative tools like 'llm_api_cost_calculator' or when not to use. No when-not or prerequisites 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?

With no annotations, the description must disclose behavioral traits. It reveals the tool is research-based and not a prediction, which is helpful. However, it doesn't mention that the tool is stateless, requires four numeric inputs (0-1), or any potential side effects. The transparency is adequate but not thorough.

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 conveys the core idea. However, it redundantly repeats the title phrase 'AI Job Exposure Score (Research-Based, Not a Prediction)' at the start. It could be more concise by removing that duplication.

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 zero annotations, no output schema, and 0% schema coverage, the description is insufficient. It does not explain the output format, detail the parameters, or provide usage context relative to the many sibling calculators. The agent lacks essential information to use the tool correctly.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage for 4 required parameters. The description vaguely mentions 'task mix' but does not explain what each parameter (routineCognitive, creativeCognitive, interpersonal, physical) means or their expected scales. The description adds little value 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 estimates an AI job exposure score based on published research and task mix. It uses a specific verb ('estimate') and resource ('AI job exposure score'). While it doesn't explicitly differentiate from sibling calculators, the unique topic makes its purpose clear.

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 estimating task exposure rather than making predictions, but it offers no explicit guidance on when to use this tool over alternatives or when not to use it. There are no references to other tools or conditions.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states that the tool calculates financial metrics based on user inputs, which implies a read-only, non-destructive operation. However, it does not mention any limitations, prerequisites, or data handling policies, leaving some behavioral uncertainty.

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 tool's purpose, inputs, and outputs. It front-loads the name and uses minimal words. While very concise, it could benefit from a more structured format (e.g., bullet points) for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations or output schema, the description should fully detail inputs and outputs. It lists three inputs (missing two) and three outputs (likely adequate). It is complete enough for a straightforward calculator but lacks explicit parameter mapping for all five required fields.

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 0% schema coverage, the description must compensate by explaining parameters. It mentions only three of five parameters ('hours saved per week', 'staff count', 'cost'), leaving hourlyCost and monthlyToolCost ambiguous. The term 'cost' could refer to implementationCost but is vague, and monthlyToolCost is omitted entirely.

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 estimates ROI and payback specifically for AI tools, distinguishing it from generic ROI calculators or other financial calculators in the sibling list. It provides a specific verb ('estimate') and resource ('ROI and payback of an AI tool'), making the purpose unambiguous.

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 lists the required inputs (hours saved per week, staff count, cost) and outputs (monthly net savings, break-even months, annual return), giving clear context for when to use this tool. However, it does not specify when not to use it or compare to alternatives like the generic roi_calculator sibling.

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

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

No annotations provided; description carries full burden. It clearly states what the tool calculates (profit, margin, ROI, fee breakdown, break-even price), implying read-only behavior. No contradictions or missing critical behavioral traits for a calculator.

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 filler. Key information front-loaded: purpose, inputs, outputs. Every word adds value.

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 5 parameters and no output schema, the description provides adequate high-level purpose but lacks full parameter details and expected output format. An agent might incorrectly guess adCost and referralRatePct behavior.

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 0%, but description only explains three of five parameters (price, COGS, size tier). It does not clarify adCost, referralRatePct, or size tier enum values beyond mentioning size tier. This leaves agents with incomplete understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool calculates Amazon FBA net profit, margin, and ROI, mentioning key inputs (price, COGS, size tier). It clearly distinguishes itself from sibling calculators by focusing on Amazon FBA specifically.

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 Amazon sellers but does not explicitly state when to use this tool versus alternatives like ecommerce_profit_margin_calculator or product_pricing_calculator. No guidance on exclusions 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?

Describes conversion and output (APY, final balance) but not behavioral details like whether all fields are required or any side effects. No annotations to supplement.

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 key information, 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?

Contributes context for output (APY, final balance) but lacks detail on exact return format. No output schema, so more needed. Adequate for a simple calculator.

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?

Description mentions nominal rate, compounding frequency, and implies deposit and years (final balance), but does not explicitly describe each parameter. With 0% schema coverage, some compensation but incomplete.

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 converts APR to APY and shows effect of compounding frequency. Specific verb and resource, distinct from sibling calculator 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?

Implies usage when you have APR and want APY, but no explicit guidance on when to use versus alternatives 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?

No annotations are provided, so the description must carry full burden. It mentions calculations but does not disclose behavioral traits such as read-only nature, precision, rounding, or assumptions (e.g., standard inch-of-fish rule). This lacks depth needed for safe invocation.

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: first provides title and summary, second specifies inputs and outputs. It is concise, well-structured, and front-loaded with key 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?

Given the tool has 4 parameters, no output schema, and no annotations, the description covers inputs and outputs adequately. However, it lacks details like formulas, default assumptions, or edge cases (e.g., maximum tank size), which could improve 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 0%, so no parameter descriptions exist in the schema. The description adds meaning by stating units (inches) and context (stocking capacity via inchesPerGallon). However, it does not individually describe each parameter or their role, leaving some ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is an aquarium volume and stocking calculator. It specifies inputs (length, width, height in inches) and outputs (gallons, litres, inch-of-fish, heater wattage), distinguishing it from other calculator siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit when-to-use or when-not-to-use guidance. While the tool is distinct among siblings, users might benefit from context like 'Use this for rectangular tanks only' or alternatives for different shapes.

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

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

With no annotations, the description must disclose behavior. It does not mention output format, rounding, precision, or handling of edge cases. The phrase 'simplify an aspect ratio' is vague.

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 short and gets the core idea across, though the phrase 'Simplify an aspect ratio' could be clearer. It is front-loaded but not 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?

No output schema exists, so the description should explain return values. It mentions 'get the ratio' and 'solve the matching height' but does not specify what is returned or how. Edge cases like non-integer ratios are unaddressed.

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 0%, so the description must compensate. It explains that width and height define the original ratio and newWidth is the desired width to compute matching height, adding meaning beyond parameter names.

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 simplifies aspect ratio and resizes while keeping it, and explains the process of entering width and height to get ratio then new width to get height. This distinguishes it from siblings like crop_factor_calculator.

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 crop_factor_calculator or print_resolution_calculator. The description does not mention exclusions or context-specific recommendations.

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

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

No annotations are provided, so the description must carry full burden. It mentions scaling by area and providing ratio and bake-time guidance, but does not disclose assumptions (e.g., pan depth consistency) or edge cases (e.g., custom shapes). Adds some context but incomplete.

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 and front-loaded with purpose. It is efficient but could benefit from a clearer structure (e.g., separate purpose from method). Still concise 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?

With no output schema and complex nested input, the description lacks completeness. It does not specify the output format (ratio, bake-time adjustment formula), assumptions (pan depth), or limitations. Insufficient for a tool with 0% schema description coverage and no annotations.

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 0% (no parameter descriptions in schema). The description adds little beyond what the schema already shows: it mentions scaling by area but does not explain how to specify dimensions for each shape (e.g., round: diameter, square: side, rectangular: width/length). Fails to compensate for low schema 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's purpose: converting recipes between round, square, and rectangular pans by area. It uses a specific verb (convert/scale) and resource (recipe), and distinguishes from sibling tools like 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 usage for recipe conversion between pan shapes but lacks explicit guidance on when to use this versus alternatives (e.g., recipe_scaler_calculator). No exclusion criteria or context for when not to use it.

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

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

No annotations are provided, so the description must convey behavioral traits. It indicates a read-only calculation ('See how much... saves'), which is appropriate for a calculator. However, it does not elaborate on the algorithm, assumptions, or that it does not modify any data, leaving some ambiguity.

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 that immediately convey the tool's purpose and key inputs. It is front-loaded with the title, and every part adds value. There is no wasted 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?

Despite having no output schema and incomplete parameter descriptions, the description provides enough context to understand the main comparison. However, missing details about the full set of inputs and the output format (e.g., whether it shows dollar savings or percentage) reduce 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 0%, so the description must explain all parameters. It only mentions three (fee, promo months, planned payment) out of six required parameters: balance, currentAprPct, and revertAprPct are not described. This incomplete coverage fails to fully clarify parameter meaning.

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: to compare savings from a 0% balance transfer versus staying with the current APR. It uses a specific verb 'See how much... saves' and identifies the resource (balance transfer calculator). This distinguishes 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 implies the use case: when evaluating a 0% balance transfer offer. It mentions specific inputs (fee, promo months, planned payment) that indicate the context. While it does not explicitly state when not to use it or specify alternatives, the context is clear enough for an agent to decide.

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

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

No annotations are provided, so the description must disclose behavioral traits. It only states the tool estimates body fat using a specific method, but does not mention that it is a read-only calculation, requires no authentication, or has any side effects. This is minimal disclosure for a computation 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?

The description consists of two succinct sentences. The first introduces the method and purpose, the second lists inputs and outputs. Every word adds value, and the structure is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six parameters, no output schema, and no annotations, the description should be comprehensive. It omits important details: units (cm vs inches), the conditional requirement of hip for females, and the exact output format beyond 'body fat and lean body mass'. These gaps hinder a user from using the tool correctly without additional inference.

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 0%, so the description must compensate. It lists five of six parameters (sex, height, neck, waist, hip) but does not mention the optional weightKg parameter or clarify units (schema uses cm, but description omits units). It also fails to explain that hip is only required for females. The description adds some context but leaves significant gaps.

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 body fat percentage using the US Navy tape-measure method, specifying inputs (sex, height, neck, waist, hip) and outputs (body fat, lean body mass). This clearly distinguishes it from sibling calculators which cover different domains.

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 instructs users to enter specific measurements to see results, implying the tool is for users with those measurements. However, it does not provide guidance on when not to use this tool or compare it to related health calculators (e.g., calorie_deficit_calculator, tdee_calculator).

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

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

No annotations are provided, so the description must carry the burden. It mentions the inputs and outcome but does not disclose behavioral traits such as what is returned (e.g., units vs revenue), error handling, or any side effects. The transparency is adequate for a simple calculator but not thorough.

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 after the title, front-loaded with purpose. It is concise, though the listing of parameters could be more precise.

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 4 required parameters, no output schema, and no annotations, the description should explain what the tool returns (e.g., break-even units, revenue) and how to interpret results. It fails to mention any output, leaving the agent uncertain about the tool's response.

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 0%, so the description must add meaning. It mentions fixed costs, variable cost per unit, and price per unit but omits targetProfit, which is a required parameter. This omission reduces the clarity of parameter 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 the tool calculates break-even point in units and revenue, using a specific verb ('calculate') and resource ('break-even point'). It distinguishes itself from sibling calculators by focusing on break-even analysis.

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 when break-even calculation is needed but provides no explicit guidance on when to use versus alternative calculators, nor any exclusions 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?

No annotations are provided, so the description must disclose behavioral traits. It states the tool calculates and returns 'exact grams and a strength chart', but does not confirm it is read-only, explain any side effects, or clarify input validations. For a calculator tool, agents may infer safety, but explicit disclosure is lacking.

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 front-loads the tool's purpose and key inputs/outputs. It is efficient with no extraneous words, though it could benefit from clarifying parameter relationships.

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 5 required parameters, no output schema, and zero parameter descriptions in the schema, the description falls short. It fails to explain the interplay between waterVolumeL, meatWeightGrams, and mode, or that sugarPct is also needed. The output only mentions 'strength chart', leaving other return value details unspecified.

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 0%, so the description must add meaning. It mentions 'water volume or meat weight' and 'salt percentage', but implies an 'or' relationship while the schema requires both waterVolumeL and meatWeightGrams. It omits explanation of sugarPct (yet required) and mode (wet/dry). This creates ambiguity and incomplete guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it calculates salt and sugar amounts for wet or dry brines by weight, using specific inputs like water volume or meat weight and salt percentage. It gives a concrete verb ('calculate') and resource ('salt and sugar for brines'), but does not explicitly differentiate from other recipe-related calculators in the sibling list.

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 brine preparation but offers no guidance on when to use this tool versus alternatives (e.g., recipe_scaler, pizza_dough_calculator). It does not mention scenarios where this tool is inappropriate or when another tool might be better suited.

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

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

No annotations provided, so description carries full burden. It describes outputs (e.g., month-by-month simulation) but does not disclose side effects or permission needs. However, as a calculator, read-only behavior is implied.

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 with a dash and list covers key features without waste. Front-loaded with title. Could be slightly more structured but 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?

Covers main outputs and simulation aspect. Missing details on interpretation of 'alive/dead verdict' and prerequisite hints, but adequate for a 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 has 0% description coverage across 5 parameters. Description mentions gross/net burn and revenue growth but does not explain individual parameters like cashBalance or monthlyExpenses.

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 startup burn rate and cash runway, with specific outputs like gross vs net burn and alive/dead verdict. It is distinct from sibling calculators by focusing on startup-specific 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 on when to use this tool over alternatives. With many financial calculator 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?

With no annotations, the description discloses all key outputs (LTV, ratio, bands, payback, gross profit). As a likely read-only calculator, no side effects are expected, but the description could explicitly state it only computes and returns results without modifying any data. However, it sufficiently informs the agent of what the tool produces.

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 lists all supported computations. It is efficient with no redundant text, though it could be slightly shortened without losing clarity.

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 lack of output schema, the description enumerates all return values (LTV, ratio, bands, payback, gross profit). For a straightforward calculator tool, this provides sufficient context for understanding what the tool returns, though it omits the exact format or structure of the result.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 4 parameters with 0% description coverage. The tool description does not explain what any parameter means (e.g., arpa, grossMarginPct, monthlyChurnPct, cac), leaving the agent to infer meaning solely from parameter names. This is a critical gap for correct invocation.

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 Customer Lifetime Value, LTV:CAC ratio with verdict bands, CAC payback months, and monthly gross profit per customer. It uses a specific verb 'Calculate' and resource, and distinguishes it from numerous sibling calculator tools by naming exact outputs.

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 LTV:CAC metrics but provides no explicit guidance on when to use it versus alternative calculators (e.g., churn_rate_calculator). There are no usage contexts, prerequisites, or exclusions 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?

No annotations are provided, so the description must carry behavioral disclosure. It reveals outputs (deficit, weekly loss, safety check) but does not disclose underlying assumptions (e.g., BMR formula, activity level) or potential edge cases. Adequate but not detailed.

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 front-loads the title and succinctly lists inputs and outputs. No redundant or misleading 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 three-parameter calculator with no output schema, the description covers inputs and key outputs (daily deficit, weekly loss, safety check). It is complete for typical use, though unit display or formula details could enhance 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 describes three numeric parameters with no descriptions (0% coverage). The tool description mentions 'goal weight' and 'target date', partially explaining goalKg and days, but currentKg is implied. No units or format details are added beyond what parameter names suggest.

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 daily calorie deficit, weekly loss rate, and safety assessment from goal weight and target date. It distinguishes itself from sibling calculators like body_fat_calculator or tdee_calculator by focusing on deficit with a deadline.

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 setting a weight loss deadline, but provides no explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned. The context is inferred rather than stated.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions the MET formula but does not discuss assumptions, limitations, accuracy, or any potential side effects. This leaves the agent uncertain about the tool's 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?

The description is concise (two sentences) and front-loads the tool's name and purpose. It avoids unnecessary detail, making it easy to digest. However, it could be slightly improved by adding more structured info without increasing length significantly.

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 absence of an output schema, the description should indicate the format of the result (e.g., 'returns total calories burned as a number'). It mentions 'estimate energy spent' but does not specify what the output looks like or cover edge cases like missing parameters.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema lacks descriptions for all parameters (0% coverage). The description lists the parameters (weight, minutes, activity) but does not provide additional meaning such as units or range context beyond what the schema's min/max values imply. For example, it does not clarify that 'met' values correspond to specific activities.

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's function: calculating calories burned using the MET formula, with specific inputs (weight, minutes, activity) and an additional feature to compare exercises. This differentiates it from sibling calculators like calorie_deficit_calculator or tdee_calculator.

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 when to use the tool (to estimate energy spent and compare exercises) but does not explicitly state when not to use it or mention alternative tools. However, the context is clear enough for an AI agent to decide.

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

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

No annotations provided, so description carries full burden. It mentions outputs (max loan, car price, rule check) but does not explain computation method, formulas, or assumptions behind the '15%-of-income rule'.

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 concise, delivering key information in two sentences without redundancy. Slightly repetitive of title, but efficient overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description gives vague output descriptions ('max loan and car price, plus a 15%-of-income rule check') and omits important parameter details, leaving gaps for a 6-parameter 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 0%, so description should clarify parameters. It names monthlyPayment, annualRatePct, termMonths, downPayment but omits required tradeIn and optional monthlyIncome (only implied by rule check). Insufficient detail.

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 'How much car can you afford?' and lists inputs and outputs. It distinguishes itself from sibling car loan calculators by focusing on affordability, but does not explicitly differentiate.

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 when wanting to determine affordable car price, but provides no guidance on when not to use it or alternatives among 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?

No annotations exist, so the description must fully disclose behavior. It mentions outputs (year-by-year curve, total loss, percent lost) but does not explain the calculation methodology (e.g., linear vs. declining balance) or assumptions. This is insufficient for a financial calculator.

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 tool's name and purpose. Every sentence adds value, and there is no redundant information. Ideal conciseness for a single-purpose calculator.

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 4 required parameters, no output schema, and a moderate complexity, the description is adequate but incomplete. It details outputs but lacks parameter explanations and calculation logic. Hovering at a minimum viable level.

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 0% schema description coverage, the description should explain parameters. It mentions 'price and depreciation rates' but does not clarify which parameter corresponds to first-year vs. annual rate, nor does it describe parameter ranges or units 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 it estimates car worth over time using inputs like price and depreciation rates. The verb 'estimate' and resource 'car worth' are specific, and the name 'car_depreciation_calculator' distinguishes it from sibling calculators like car loan or lease 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 usage for estimating depreciation but does not explicitly state when to use this tool versus alternatives like car_affordability_calculator. No when-not or alternative guidance is provided, only a generic statement on entering parameters.

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

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

With no annotations, description carries full burden. It mentions estimating monthly payment and showing splits, but does not disclose any limitations, assumptions (e.g., no acquisition fee), or behavioral traits. Adequate for a straightforward calculator but lacks depth.

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 with a dash, front-loaded with the tool's name and purpose. Efficient, 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?

With 5 required params, no param descriptions, no output schema, and many sibling calculators, the description is minimally adequate. It does not explain the money factor concept, specify that sales tax is an input, or provide units/ranges beyond schema. Leaves gaps that require additional context.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% with no parameter descriptions. Description lists cap cost, residual, term, and money factor as inputs but omits salesTaxPct, which is a required input. This omission could mislead agents. No additional meaning provided beyond names.

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 is a car lease payment calculator using money factor, listing inputs (cap cost, residual, term, money factor) and outputs (depreciation, finance split, sales tax, APR). It distinguishes itself from sibling calculators like car_loan_calculator and lease_vs_buy_car_calculator by focusing on money factor and lease specifics.

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. It does not mention that it is intended for leases with money factor (not interest rate) or contrast with car_loan_calculator or lease_vs_buy_car_calculator. Users must infer from the name and description.

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

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

No annotations are provided, so the description carries the burden. It describes outputs (monthly payment, amortization, etc.) and implies a read-only calculation. For a calculator, this is transparent enough.

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 main purpose is front-loaded. Every sentence adds value.

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 tool with 6 required parameters and no output schema, the description is too brief. It does not guide parameter values or provide examples, leaving the agent under-informed.

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 0%, but the description mentions 'including sales tax and trade-in' which hints at parameters. However, it does not explain individual parameters like annualRatePct or termMonths, leaving ambiguity for the agent.

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 monthly car payment including sales tax and trade-in, and provides amortization schedule, total interest, and cost of ownership. It distinguishes from sibling calculators by specifying the inclusion of sales tax and trade-in.

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 car loan calculations with tax and trade-in, but does not explicitly state when to use versus alternatives or when not to use. No exclusions or alternative tool names 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?

With no annotations provided, the description must convey all behavioral traits. It explains that the tool calculates and displays breakdowns and blended APY, which covers basic behavior. However, it does not disclose assumptions (e.g., compounding frequency, reinvestment), edge cases, or whether it is purely computational (read-only). This is adequate but not comprehensive.

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 concise (two sentences) and front-loaded with a title and dash. Every sentence adds value. However, it could be slightly more structured by separating purpose from outputs, but overall it is efficient and avoids 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?

The tool has 4 required parameters and no output schema or annotations. The description mentions three outputs (year-one interest, per-rung breakdown, blended APY) but does not specify input constraints or assumptions. For a calculator tool, this provides a moderate level of completeness, but additional detail on parameter usage or output format would be warranted.

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 0%, so the description must clarify each parameter. It mentions 'principal' implicitly with 'split your savings' and 'rungs' with 'staggered-maturity CDs', but 'baseApy' and 'step' are undefined. The description does not map these terms to the schema properties, leaving the agent to guess their meaning and valid ranges.

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: build a CD ladder by splitting savings across staggered-maturity CDs. It specifies the outputs: year-one interest, per-rung breakdown, and blended APY. This distinguishes it from sibling calculators like apy_calculator or compound_interest_calculator, which serve different financial 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?

The description implies usage for constructing a CD ladder but provides no explicit when-to-use or when-not-to-use guidance. There is no mention of alternatives among the many sibling financial calculators, leaving the agent to infer context from the tool's name and description 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?

No annotations are provided, so the description must disclose all behavioral traits. It implies read-only calculation but does not explicitly state if it modifies data, requires authentication, or has side effects. The mention of 'compounding conversion' and 'implied average customer lifetime' adds some behavioral context beyond mere calculation, but overall it is adequate but not thorough.

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 front-loads the title and effectively summarizes the tool's capabilities without unnecessary words. Every part adds value, and the information density is high.

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 there is no output schema, the description outlines key outputs (monthly/ annual churn, revenue churn, net revenue retention, implied lifetime), which is helpful. However, it omits any assumptions, constraints, or the exact format of results, leaving minor gaps for a complete understanding.

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 0%, so the description must compensate by explaining parameter meanings. The description does not describe each parameter individually; it only hints at the overall calculation. Parameter names like 'startingCustomers' and 'expansionMRR' are somewhat self-explanatory, but no additional context is provided, leaving the AI to guess exact 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 the tool calculates monthly and annual customer churn, revenue churn, net revenue retention, and implied customer lifetime. It uses a specific verb ('calculate') and names distinct resources, making it easy for an AI to understand the primary function. The title and description together strongly differentiate this from sibling calculators like cac_ltv_calculator.

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 cac_ltv_calculator or saas_mrr_growth_calculator. It does not mention prerequisites, scenarios, or exclusions, leaving the AI to infer usage solely from the tool name and purpose.

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

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

No annotations are provided, so the description carries the transparency burden. It describes the tool as an estimator producing itemized fees and cash to close, but does not detail return format or side effects. For a calculator, this is acceptable but not highly transparent.

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 key outputs. It avoids redundancy but could benefit from brief parameter explanations. Nonetheless, it 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?

For a calculator with 7 required parameters and no output schema or annotations, the description provides a high-level overview but lacks detail on input constraints, output format, and typical scenarios. Parameter names partially compensate, but completeness is adequate but not strong.

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 0%, and the description only vaguely references fee categories (origination, appraisal, title, prepaid) without mapping to specific parameters or explaining their semantics. Seven required parameters are left mostly unexplained, requiring the agent to infer from names.

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 estimates US mortgage closing costs, listing specific fee categories (origination, appraisal, title, prepaid) and cash to close. It distinguishes from sibling mortgage calculators (e.g., overpayment, piti) by focusing on closing costs.

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?

Description indicates usage 'before you buy,' which is clear context for home buyers. It does not explicitly list exclusions or alternatives among siblings, but the specificity of 'closing costs' implicitly guides appropriate 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?

No annotations are provided, so the description carries full burden for behavioral traits. It only describes the conceptual calculation without disclosing behavior such as whether it's read-only, side effects, or any limitations. For a calculator tool, users can infer it's safe, but the description does not explicitly state this.

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 very concise, consisting of two sentences with the key concept front-loaded. However, the phrase 'Mind the gap' is somewhat cryptic and may not add clarity. The structure is efficient but could be slightly improved by removing ambiguous phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and 5 required parameters, the description lacks explanation of how to use inputs or what the result looks like. It does not compensate for the low schema coverage, leaving gaps for an agent to know correct usage.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% because the description does not mention any of the 5 input parameters. It only explains the overall concept, leaving the agent to rely solely on parameter names in the schema. No additional meaning or format details 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 states it finds the Coast FIRE number, explaining what that means ('amount you need invested today so it grows to your FIRE target by retirement with zero further contributions'). The specific term 'Coast FIRE' and the 'zero further contributions' detail distinguish it from the sibling 'fire_calculator', which likely calculates traditional FIRE with ongoing contributions.

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 calculating Coast FIRE numbers, but does not explicitly mention when to use this tool versus alternatives like the sibling 'fire_calculator'. There is no exclusionary guidance or context on when not to use it.

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

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

With no annotations provided, the description carries the full burden. It hints at output ('balance grow year by year', 'pure interest') but does not specify exact return structure, accuracy, compounding frequency, or any side effects. This is minimal behavioral disclosure.

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 long with no redundancy. It front-loads the core purpose and then adds value about the output. However, it could be more structured, e.g., separating purpose from output details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should describe the return format more explicitly (e.g., JSON with yearly breakdown). It also lacks error handling details or assumptions like compounding frequency. The complexity (4 required parameters, financial calculation) demands more 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 0%, and the description does not explain any parameter meaning, units, or constraints beyond what is implied by the property names. The user must infer that 'annualRatePct' is a percentage and 'years' is time duration. No clarification of the optional parameters or how they interact.

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 verb ('calculate'), resource ('compound interest with monthly contributions'), and output ('see your balance grow year by year and discover exactly how much of your final balance is pure interest'). The title and description together distinctly identify the tool's function among many sibling 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 guidance on when to use this tool versus alternatives like savings_goal_calculator or apy_calculator. It does not mention any prerequisites, limitations, or contexts where the tool is or isn't 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?

No annotations provided, so description must convey behavior. It states it's a calculation tool (harmless) but omits details like input validation, error handling, or output precision. Lacks depth for a non-annotated 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?

Two succinct sentences with no redundant words. Key details front-loaded: tool name, purpose, inputs, outputs. Highly 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?

Provides enough for a simple calculator: input types and outputs (cubic yards, feet, bag count). However, misses parameter descriptions for waste and bag yield, and lacks output schema or note on rounding. Adequate but with 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 has 0% parameter descriptions. Description explains three parameters (length, width, thickness) but omits wastePct and bagYieldFt3, which are required. Does not fully compensate for missing schema details.

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's function: calculate concrete needed for slabs, footings, or pads. It uses specific verbs ('calculate') and resources ('concrete'), and distinguishes from numerous sibling calculators by niche.

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?

Description implies when to use (for concrete volume and bag count) but provides no explicit when-not or alternative tools. It lacks exclusions or context, relying on the tool's obvious purpose.

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

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

No annotations are provided, so the description carries full burden. It states it computes the equivalent 1099 gross rate from W-2 inputs, implying a forward calculation. It does not disclose edge cases (e.g., zero salary, negative values) or if reverse calculation is supported. The behavior is standard for a calculator, but more details on assumptions or limitations would be beneficial.

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 well-structured and front-loaded with the tool's purpose. Every part adds value: it names the comparison, lists inputs, and states the output. 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 zero schema description coverage and no output schema, the description should provide more complete context. It explains inputs but not the output format (e.g., whether the equivalent rate is yearly or hourly). It also omits assumptions like tax rates or self-employment tax. The sibling tools are many calculators, so more detail would help the agent differentiate and use 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 description coverage is 0%, so the description must add meaning. It lists the parameters: salary, employer FICA, benefits, and PTO, but does not elaborate on units or precise definitions (e.g., employerFicaPct is a percentage, but description says 'employer FICA' without specifying percentage of salary). It adds some context but not enough to fully compensate for the lack of 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 clearly states it compares W-2 job to 1099 contract work and calculates the equivalent 1099 gross rate needed to break even. It distinguishes itself from sibling calculators like salary_to_hourly_calculator or freelance_hourly_rate_calculator by focusing specifically on the employer-provided vs contractor compensation comparison, including benefits and PTO.

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 tells when to use this tool: when comparing a W-2 job to 1099 contract work to find the break-even rate. It implies usage for evaluating offers but does not explicitly state when not to use it or mention alternatives. The context is clear enough for an agent to decide, but a mention of alternatives (e.g., if you already have contractor rate and want to compare) would improve 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?

No annotations provided. The description does not disclose behavioral traits beyond the basic purpose (e.g., that it's a stateless calculator returning a single number, no side effects, no data persistence). It lacks details like whether it handles unit conversions or precision.

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 with a colon, efficiently conveying purpose. It is front-loaded with the tool name and outcome. Minor fluff ('See what your car truly costs to drive') is acceptable.

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 a calculator tool with no output schema, the description adequately implies the output (cost per mile). It covers the required inputs and the formula. Could explicitly state output format, but sufficient 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 coverage is 0%. The description lists the parameters (fuel, maintenance, insurance, etc.) but does not explain units or format (e.g., yearly total in dollars). It adds minimal meaning beyond the schema's names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it calculates cost per mile based on annual costs (fuel, maintenance, insurance, depreciation, loan payments). It distinguishes from sibling calculators like car_affordability_calculator or car_lease_calculator.

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 when you want to compute cost per mile, but does not explicitly state when not to use or provide alternatives among the many sibling calculators. No exclusions 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?

With no annotations, the description carries full burden but only vaguely mentions returning 'months' and 'decades/multiples'. It does not detail the output format (e.g., does it return total interest, a comparison table?), nor disclose if it is read-only or requires authentication.

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-loads the core purpose, and contains no 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?

The tool has 4 parameters and no output schema, yet the description fails to explain what exactly the calculator returns (e.g., payoff months, total interest, comparison of both strategies). It also lacks details on assumptions like minimum payment calculation.

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 0%, but the description only mentions 'balance', 'APR', and 'monthly payment' without explaining parameter names, constraints, or the optional 'targetMonths'. It adds minimal value over 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 calculates payoff months and compares fixed vs minimum payments, distinguishing it from generic debt calculators by focusing on the minimum-payment trap. However, it does not explicitly differentiate from similar siblings like debt_payoff_calculator.

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 credit card payoff scenarios and highlights the minimum-payment trap, but it provides no explicit guidance on when to use vs. alternatives, nor 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?

No annotations provided, so description carries full burden. It states that the tool converts focal length and aperture to equivalents and field of view, but does not disclose any potential side effects, authentication needs, or rate limits. Adequate for a simple calculator.

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 after the title, 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?

For a 5-parameter calculator with no output schema, the description explains inputs and outputs ('get equivalent focal, aperture, and field of view') but lacks details on the relationship between parameters and output format. Adequate but not 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 description coverage is 0%. The description adds meaning by mentioning 'focal length, aperture, and sensor' which map to some parameters, but does not explicitly describe all 5 parameters (cropFactor, sensorWidthMm are omitted). Provides partial compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource: 'Convert focal length to a full-frame equivalent by crop factor.' It clearly distinguishes from other calculator tools by focusing on crop factor conversion.

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 vs alternatives (e.g., depth_of_field_calculator). Usage is only implied by the title and description.

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

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

No annotations are provided, so the description carries full responsibility. It warns about the true cost of longer terms, which adds some behavioral insight, but fails to disclose the output format, any assumptions (e.g., fixed interest, no fees), or state whether data is stored. This is insufficient for a calculator with financial implications.

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 concise sentences, front-loaded with the tool's name and purpose. 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 complexity of comparing multiple debts with a consolidation loan, the description is minimal. It lacks details on the output (e.g., total interest, monthly payment comparisons) and does not explain how 'true lifetime numbers' are calculated. Without an output schema, more context is 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?

The input schema has 0% description coverage. The description does not mention any parameters, leaving the agent to infer meanings from property names alone (e.g., balance, aprPct, minPayment). It adds no value 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 compares current debts against a consolidation loan and highlights the risk of longer terms costing more. It distinguishes itself from sibling tools like debt_payoff_calculator by focusing specifically on consolidation.

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 considering debt consolidation by saying 'See how your current debts compare against one new consolidation loan.' However, it does not explicitly state when to use this tool versus alternatives, nor does it mention when not to use it.

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

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

No annotations provided, and description lacks details on calculation assumptions, edge cases, or behavior. It only mentions outputs (interest saved, months sooner) but not how results are computed or any limitations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Relatively concise single sentence, but it repeats the title and could be more efficient. Structure is okay but lacks front-loading of key purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and a complex input (array of objects), the description is insufficient. It does not describe the output format, how to interpret results, or any constraints like maximum debts.

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 0%, and the description does not explain any parameters (debts array fields, extraMonthly, strategy enum). Meaning beyond schema is minimal.

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 compares avalanche and snowball debt payoff strategies and shows interest savings and months sooner. However, it claims 'side by side' comparison, while the input schema only accepts a single strategy, potentially misleading.

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 other debt calculators like credit_card_payoff_calculator or debt_consolidation_calculator. No prerequisites or exclusions 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?

No annotations are provided, so the description must disclose behavioral traits. It describes a standard calculation, which is non-destructive and read-only, but does not explicitly state this. It adds no behavioral context beyond the obvious 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?

The description is a single sentence that efficiently conveys purpose and key inputs/outputs. It could be slightly more structured (e.g., listing parameters separately) but remains clear 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?

For a calculator tool without an output schema, the description adequately covers inputs and outputs. It explains what the tool does and what results are produced, but lacks explicit units or edge-case disclaimers.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 7 parameters with zero descriptions (0% coverage). The description names 5 of them (deck length, width, board width, gap, board length) and explains their role in the calculation. It omits wastePct and pricePerBoard, but still provides significant semantic 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 it calculates how many deck boards are needed, lists specific inputs (deck length, width, board width, gap, board length) and outputs (area, linear feet, board count, total cost). It distinguishes itself from sibling calculators by being specific to deck boards.

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?

Usage is implied by being a deck board calculator, but no explicit guidance on when to use this tool versus other calculator tools, nor any mention of prerequisites or when not to use it.

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

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

No annotations provided, so description must cover behavioral traits. It describes a pure calculation with no side effects, but omits input units and output structure beyond 'in meters'. Adequate but not thorough.

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, concise and front-loaded. However, the brevity sacrifices completeness, earning a middle score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 4 required numeric parameters, no output schema, and no annotations, the description does not fully explain inputs or outputs. Missing the circleOfConfusionMm parameter and output format 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 description coverage is 0%, and the description only mentions three of four required parameters (omits circleOfConfusionMm). No explanation of parameter meanings, units, or default behavior.

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 name, title, and description clearly state it calculates depth of field and hyperfocal distance from specific inputs. It distinguishes itself from sibling calculators like crop_factor_calculator.

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. other photography calculators or alternatives. The description does not mention exclusions 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?

No annotations exist, so the description must carry the burden. It states 'project future value and total growth' but does not explain assumptions, output format, or whether it is a simulation or exact calculation. It lacks details like compounding frequency or dividend reinvestment assumptions.

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 tool's purpose and required inputs. It is front-loaded with the name and benefit, though it could benefit from bullet points or clearer structure for the parameters.

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 5 parameters and no output schema or annotations, the description is insufficient. It does not explain what the output values represent, the time horizon (years), or any underlying models (e.g., annual compounding). A more complete description would include return structure and 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 coverage is 0%, and the description only mentions 'dividend yield, price growth, and yearly contributions', omitting 'principal' and 'years'. It does not clarify units (e.g., percentages) or link parameters to the projection, failing to compensate for missing 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 clearly states it is a DRIP calculator that projects future value and total growth from reinvested dividends, using specific inputs. However, it does not explicitly distinguish from sibling calculators like compound_interest_calculator, though the focus on dividends differentiates it.

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?

It tells the user to enter dividend yield, price growth, and yearly contributions, providing some usage context. However, it does not specify when to use this tool versus alternatives (e.g., compound_interest_calculator) or mention any prerequisites 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?

With no annotations, the description takes on the burden of behavioral disclosure. It clarifies the method (AKC, size-adjusted) and corrects common misconceptions. It does not mention any limitations or side effects, but the core computational approach is well explained.

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 long, direct, and front-loaded with key information. Every part adds value, with no redundancy or filler.

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 a simple calculator with no output schema. The description explains input and method but does not describe the output format (e.g., a number representing human years). Given the simplicity, this is a minor gap but still leaves the agent guessing about the return value.

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 0%, but the description names both parameters ('age and size') and explains their role in the conversion. It does not elaborate on the enum values for sizeClass or the age range constraints, so it partially compensates for the missing 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 clearly states the tool converts dog age to human years using the AKC method adjusted for body size, debunking the old multiply-by-7 myth. The name 'dog_age_calculator' is distinct among sibling calculators, though not explicitly differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'Enter age and size for a real estimate,' which implies when to use it. However, it does not provide explicit when-not-to-use guidance or mention alternative calculators for related tasks, such as puppy weight estimation.

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

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

No annotations exist, so description must disclose behavior. It only states what the tool calculates, not how it behaves (e.g., stateless, no side effects, uses default assumptions). Does not reveal rate limits, caching, or external data usage.

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, both front-loaded with key info. First sentence provides a title and action, second adds features. No redundant or filler 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 simple calculator with no output schema, the description does not describe return values, output format, or how results are presented. Missing details like whether it returns numbers, percentages, or dollar amounts.

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 0% and description does not explain parameters 'price' and 'downPct'. It implies down payment percentage but does not define the format, range, or meaning. The phrase 'multiple down payment scenarios' is vague about how to provide them.

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 tool calculates down payment, loan size, and PMI status, with comparison of multiple scenarios. It uses specific verbs ('Calculate', 'See') and distinguishes itself from other calculators by focusing on down payment and PMI threshold.

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. Among many financial calculators, it lacks indications like 'Use when you need to determine down payment percentage or PMI eligibility.' The description does not mention when not to use it.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the calculation function and fails to mention any edge cases, side effects, or limitations (e.g., no distinction between wall and ceiling area despite the parameter name 'wallArea'). No contradictions with annotations as none exist.

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 concise (two sentences) and front-loads the purpose. It could be slightly more structured (e.g., bullet list of inputs/outputs), but overall it is efficient 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 no output schema, the description lists output types (sheets, screws, mud, tape) which is helpful but lacks detail (e.g., units, formulas). For a calculator tool, this is minimally adequate but leaves an agent guessing about the exact format or assumptions (e.g., whether ceiling is included in wallArea).

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 description mentions inputs (wall/ceiling area, waste percent, sheet size) but adds little beyond the schema parameter names. Schema coverage is 0%, so the description should compensate with unit hints, constraints, or examples; it does not. There is a mismatch: description says 'total wall and ceiling area' but parameter is named 'wallArea', potentially confusing.

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 drywall sheets needed for a room, listing specific outputs (sheets, screws, mud, tape). It uses a specific verb ('Calculate') and resource ('Drywall Sheet Calculator'), distinguishing it from sibling calculators like concrete_calculator or paint_calculator.

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 what inputs to enter but provides no guidance on when to use this tool versus alternatives. Among many sibling calculators, there is no explicit when-to-use or when-not-to-use advice, leaving the agent to infer usage from the name 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?

No annotations provided. Description states 'Calculate instantly', implying a read-only operation. It doesn't disclose side effects, but for a calculator this is acceptable. Could mention no data storage or modification.

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 action and purpose. No wasted words. Efficiently conveys core functionality and thresholds.

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 calculator with 3 numeric inputs and no output schema, the description is fairly complete: it states inputs (implied), calculation type, and comparison thresholds. Could mention output format (e.g., ratios as percentages).

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 0% description coverage. Description does not explain parameters individually (housingPayment, otherMonthlyDebts, grossMonthlyIncome) beyond the tool's general purpose. Agent cannot infer parameter types or constraints from description 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 it calculates front-end and back-end DTI ratios, using specific verb 'Calculate' and resource 'Debt-to-Income Ratio'. While it doesn't explicitly differentiate from sibling calculators, the DTI focus is distinct enough.

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 comparing debt load against thresholds (36%, 43%, 50%), but lacks explicit guidance on when to use versus alternatives like debt_consolidation_calculator or debt_payoff_calculator. No 'when not to use' or alternative suggestions.

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

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions calculating margins and seeing contribution vs fully-loaded margins, but does not explain what the output looks like, whether there are side effects, or how invalid inputs are handled. The description is insufficient for a mutation tool with zero annotation coverage.

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, information-dense sentence that efficiently communicates the tool's purpose and key cost components. It uses a dash to separate the main function from the additional detail about margin types, but remains concise with 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 has 8 required parameters, no output schema, and no annotations, the description is incomplete. It does not describe the return format, how margins are computed, or what 'contribution vs fully-loaded margin' means in practice. Users lack sufficient context to interpret the tool's output.

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 0% schema description coverage, the description must compensate. It mentions COGS, shipping, packaging, payment fees, and ad spend, but does not explicitly list or define all 8 parameters (e.g., platformFeePct, returnsAllowancePct). The description adds partial meaning but is insufficient given the lack of 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 clearly states the tool calculates true ecommerce profit margin, listing specific cost components (COGS, shipping, packaging, payment fees, ad spend) and distinguishes between contribution and fully-loaded margin. This is a specific verb-resource combination that differentiates it from sibling calculator 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 does not provide explicit guidance on when to use this tool versus alternative calculators like margin_markup_calculator or cac_ltv_calculator. While the focus on ecommerce profit margin is implied, the description lacks when-not-to-use and alternative recommendations.

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

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

No annotations are provided, so the description carries the full burden. It does not mention that the tool is stateless, read-only, or has no side effects. While it's a calculator and that might be inferred, the description should explicitly state that it does not modify any state or require authentication.

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, zero wasted words. The first sentence states the purpose, the second explains inputs and outputs. Front-loaded with the key action.

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?

No output schema exists, but the description mentions the outputs ('cost per day, month, and year'), which is sufficient for a simple calculator. It does not cover edge cases like zero hours or zero watts, but the schema constraints handle those.

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 0%, so the description must compensate. It explains the three parameters: 'watts', 'hours per day', and 'your kWh rate', clarifying that 'rate' is the cost per kWh. This adds meaning beyond parameter names, though it could be more precise about units (e.g., dollars, cents).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'calculate' and clearly identifies the resource ('appliance electricity cost') and the output (cost per day, month, year). The tool name and description together make it unmistakably distinct from sibling calculators like EV charging cost or gas vs electric car.

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 the purpose: determining the running cost of any appliance. While it doesn't enumerate exclusions or alternative tools, the context is clear and the tool's scope is well-defined. No sibling tool does exactly this, so implicit guidance is sufficient.

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

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

With no annotations, the description bears full burden. It discloses the tool adds FICA, benefits, overhead and shows total and multiple, but fails to mention side effects, auth needs, or output format. Adequate but incomplete for a calculator.

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 efficiently conveys the tool's purpose and key inputs. 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?

With 4 undocumented parameters, no output schema, and no annotations, the description is insufficient. It fails to explain parameter semantics or output format, leaving significant gaps for an agent using the 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 0%, so description must compensate. It mentions salary, FICA, benefits, overhead but does not clarify units (e.g., percentages vs amounts) or provide parameter-specific guidance. Minimal added value over parameter names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('calculate') and resource ('true, fully loaded cost of an employee beyond base salary'), distinguishing it from sibling calculators like contractor_vs_employee_calculator. It clearly defines the scope.

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 calculating full employee cost but does not explicitly state when to use or avoid this tool, nor mention alternatives. It lacks explicit usage 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?

No annotations exist, and description does not disclose behavioral aspects beyond fee details. Missing info on permissions, side effects, output format, or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is concise with clear purpose and fee breakdown. Could be improved by integrating parameter hints but remains 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?

No output schema and description does not explain return values. Parameter explanations are missing, making the tool less complete for first-time users.

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 6 parameters have no descriptions in the schema (0% coverage). The description does not explain what each parameter represents (e.g., cogs, processing rates). OffsiteAds enum values are not clarified.

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 Etsy fees, net proceeds, and break-even price. It distinguishes itself from sibling calculators by explicitly naming the platform (Etsy) and providing a fee breakdown.

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 instructions on when to use this tool vs alternatives like ecommerce_profit_margin_calculator. Usage is implied for Etsy listings, but 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?

No annotations are provided, so the description carries the full burden. It indicates a calculation output but does not explicitly state it's read-only or non-destructive. Given it's a calculator, a score of 3 is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the title and purpose. Every word is useful; 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 7 required parameters, no output schema, and no annotations, the description is too sparse. It does not explain the return format, error handling, or typical ranges, leaving the agent with insufficient context to use the tool confidently.

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 0%, so the description must explain parameters. It mentions 'battery size, charge window, and rates' but fails to define 'efficiency', 'milesPerKWh', or provide units and cardinality. Many parameters are left ambiguous.

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 EV charging costs at home or public chargers, with specific mention of inputs. It distinguishes itself from sibling calculators by focusing on EV charging costs, but does not explicitly differentiate from similar tools like 'electricity_cost_calculator'.

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 when wanting to compute charging costs, but provides no explicit guidance on when not to use this tool or suggests alternatives among 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?

No annotations present, so description must fully disclose behavior. It only states high-level purpose without detailing assumptions (e.g., post spacing rounding, fractional posts, cost inclusion). Inadequate for a tool with 8 parameters and no output schema.

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 with key information, no redundancy. However, could be structured to list inputs and outputs more explicitly for faster 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 8 parameters, no output schema, and no annotations, the description lacks critical details about return format, error handling, and interpretation of results. Insufficient for reliable agent usage.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% parameter description coverage. Description only names three of eight parameters (run length, post spacing, picket width) and omits units and explanations for gapIn, railsPerSection, and price fields. Fails to fully compensate for missing 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?

Description clearly states verb (calculate), resource (fence materials), and specific outputs (posts, rails, pickets, optional cost). Distinguishes it from sibling calculators like deck_boards_calculator or concrete_calculator.

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?

Description implies usage for fence material estimation but provides no explicit guidance on when to use vs. alternatives (e.g., deck_boards_calculator). No exclusions or context for 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?

No annotations are provided, so the description carries full burden. It only states the calculation outcomes without addressing read-only behavior, rate limits, or side effects. This is insufficient for a calculator 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?

The description is a single sentence that front-loads the purpose. It is efficient but could be structured to separate inputs and outputs more clearly.

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 no output schema, the description mentions return values (pounds per feeding and per season), which is sufficient for a simple calculator. No output schema needed here.

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 0% description coverage, but the description adds meaning by mapping parameters to real-world concepts: lawn size, target nitrogen rate, bag N number, and number of applications. This compensates for missing 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 clearly states the tool's purpose: calculating fertilizer spread amounts based on lawn size, target nitrogen rate, and bag N number. It distinguishes itself from sibling calculators like grass_seed_calculator by specifying it's for fertilizer.

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 you need to calculate fertilizer amounts but does not explicitly state when to use vs. alternatives or when not to use. It lacks guidance on prerequisites or edge cases.

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

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

With no annotations, the description should disclose behavioral traits. It only states it calculates values, but omits details like whether it uses a simple formula, accounts for inflation, or any limitations. The agent lacks insight into tool behavior.

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 short but repeats the title. It uses a single compound sentence that is moderately clear, though slightly redundant. Could be more streamlined without losing meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description does not specify what the tool returns (e.g., a number, age, year, or table). For a complex financial calculation, this omission significantly impairs an agent's ability to invoke and interpret results 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 description coverage is 0%, but the description only mentions 3 out of 6 parameters (savings, expenses, return rate). It does not explain currentAge, annualSavings, or withdrawalRatePct, nor units or format. This fails to compensate for the schema's lack of 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 identifies the tool as a FIRE calculator for early retirement planning, specifying its purpose (calculate FIRE number and years to retirement) and listing key inputs. It stands out among sibling calculators focused on other domains.

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., other retirement calculators). No prerequisites or exclusions provided, leaving the agent to infer applicability.

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

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

No annotations are provided, and the description does not disclose behavioral traits such as rounding assumptions, return format, or any side effects, though it is a calculator and likely read-only.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words; purpose and inputs are front-loaded, making it easy to scan.

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?

No output schema is provided, and the description fails to describe the return value (e.g., total boxes, cost breakdown), leaving the agent uncertain about the result format.

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 description enumerates all five parameters (length, width, waste percentage, box coverage, price per box), adding basic meaning beyond the schema names, but lacks details on units, ranges, or edge cases.

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 how many boxes of flooring to buy and the total cost, distinguishing it from sibling calculators like tile_calculator or concrete_calculator.

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 lists required inputs but does not explicitly state when to use this tool over alternatives or provide exclusion criteria.

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

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

With no annotations provided, the description carries the full burden. It discloses that the tool accounts for taxes, business expenses, and profit margin, which are key behavioral traits. However, it does not describe any side effects, constraints on inputs (e.g., acceptable ranges beyond obvious), or what happens with invalid inputs. It also omits the output format (e.g., number, currency). This is adequate but not thorough.

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 front-load the purpose and key factors. Every word adds value: the title is restated, then the calculation factors are listed, and the goal ('hit your income goal') is stated. No unnecessary 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 tool has 6 required parameters, no output schema, and no annotations, the description should explain what the tool returns and any behavioral nuances. It tells what it calculates and the input factors but does not describe the output (e.g., hourly rate value) or mention constraints like tax rate cap. This is somewhat incomplete for a tool with many inputs and no structured output documentation.

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 0%, so the description must compensate. It mentions 'desired annual income, annual business expenses, tax rate, billable hours per week, work weeks per year, profit margin' implicitly by naming the factors considered. However, it does not explicitly list all six parameters or explain their semantics (e.g., that taxRatePct is a percentage between 0 and 60). The description adds some value but leaves gaps for parameters like tax rate and profit margin ranges.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool calculates a freelance hourly rate considering taxes, expenses, and profit margin. It uses specific verbs ('calculate', 'find out') and names the resource ('hourly rate'). Since sibling tools are all different calculators, this description differentiates well by specifying the exact calculation context.

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 when-to-use or when-not-to-use guidance. It does not mention alternatives among the many sibling calculators, nor does it advise on prerequisites like knowledge of desired annual income or expenses. The agent is left to infer usage based solely on the tool's name and one-line purpose.

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

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

With no annotations, the description must fully disclose behavior. It lists the computed outputs (yearly fuel cost, savings, break-even, 5-year totals) but does not explain how the optional evPricePremium parameter is used or the exact output format. This is adequate but not completely transparent.

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 tool's purpose and outputs. It is concise, though it could be slightly better structured (e.g., listing parameters separately).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 6 parameters, no output schema, and no annotations. The description covers the core purpose and expected outputs, but it omits details about the optional parameter and does not explain key inputs like kWhPerMile. This is sufficient for a simple calculator but leaves gaps for precise agent usage.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. However, it only generically mentions 'miles, MPG, and rates' without describing each of the 6 parameters individually. It fails to explain kWhPerMile or the optional evPricePremium, leaving ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a gas vs electric car cost calculator that compares yearly fuel costs and provides annual savings, break-even years, and 5-year totals. This makes the purpose highly specific and distinguishes it from sibling calculators like ev_charging_cost_calculator.

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 when comparing gas vs electric car costs but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it. Given many sibling calculators, this lack of explicit direction is a 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?

No annotations are provided, so the description carries the full burden. It mentions the scope (annual cost comparison including taxes, benefits, fees) but does not disclose behavioral traits such as that all 8 parameters are required, the output format, or any assumptions. The description is too minimal to inform the agent about required inputs or calculation behavior.

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 30-word sentence that efficiently conveys the tool's main function. It is front-loaded with the tool name. However, it could be slightly longer to include essential behavioral context without losing conciseness.

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 complexity (8 required parameters, no output schema, no annotations), the description is insufficient. It does not explain what output the calculator produces, whether a breakdown is provided, or any assumptions (e.g., tax rates). For a comparison tool, the description should clarify usage context more thoroughly.

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 0%, so the description must compensate. However, it only gives generic terms ('employer taxes, benefits, and platform fees') without mapping to specific parameters. Parameter names like 'eorEmployerBurdenPct' are not explained, leaving ambiguity. The description adds little value beyond what the names imply.

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: comparing annual costs of a US W-2 employee, international contractor, and EOR hire. It mentions specific cost components (employer taxes, benefits, platform fees) and distinguishes it from sibling calculators like 'employee_cost_calculator' or 'contractor_vs_employee_calculator' by explicitly naming the three hiring scenarios.

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. For example, a user comparing only US employee costs might be better served by 'employee_cost_calculator'. The description lacks any exclusion criteria or context for appropriate 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?

With no annotations, the description states it calculates VRAM and shows GPU fit, but does not disclose internal assumptions, limits, or behavior such as how overheadPct is applied or whether all GPUs are considered. It is adequate but lacks depth.

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 quickly conveys purpose and scope, with no unnecessary 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 no output schema and no annotations, the description leaves significant gaps: it does not explain the output format, how GPU fit is determined, or what overheadPct represents. Users lack full context for usage.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but description only mentions parameter count and precision in text, not overheadPct. It adds no extra meaning beyond parameter names, leaving overheadPct unexplained.

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 VRAM needed for LLMs by parameter count and precision, then matches to GPUs. It distinguishes from sibling calculator tools by specifying its focus on model size and GPU fit.

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 when needing VRAM requirements and GPU fit, but does not provide explicit when-to-use or when-not-to-use guidance, nor does it compare with related siblings like llm_api_cost_calculator.

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?

Without annotations, the description only reveals the basic calculation function. It does not disclose if the tool is idempotent, read-only, or has side effects. For a calculator, this is minimally adequate but not transparent.

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 purpose and usage. It is relatively concise, though it front-loads the tool name in a title-like format. 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 tool has 4 parameters and no output schema, the description should explain the output format (e.g., how bags are calculated). It says 'get pounds required and bags to buy' but lacks specifics on rounding or return structure.

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 0%, yet the description only partially covers parameters. It mentions area and seeding rate but omits bagLbs as an input. The description confuses output (bags to buy) with input (bag size parameter).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool calculates grass seed needs based on area and rate, specifying outputs (pounds and bags) and modes (new or overseed). It uniquely identifies the tool among sibling 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?

No explicit when-to-use or when-not-to-use guidance is provided. The description implies use for lawn seeding but does not mention prerequisites, alternatives, 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?

No annotations exist, so the description must disclose behavioral traits. It implies a read-only calculation but does not explicitly state that no data is modified, nor does it address permissions or limits. The description is adequate but lacks explicit safety assurances.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.