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 the tool 'Generate[s]' but doesn't disclose behavioral traits such as computational requirements, output format, whether it's read-only or mutative, error handling, or rate limits. The description is minimal and lacks essential operational context.

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

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

The description is a single, efficient sentence with zero waste. It is front-loaded with the core purpose and includes key features (confidence intervals, risk analysis) without unnecessary elaboration.

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 the input schema (4 parameters with nested objects) and no annotations or output schema, the description is inadequate. It doesn't explain the tool's behavior, output, or how to interpret results like confidence intervals, leaving significant gaps for an AI agent.

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

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

Schema description coverage is low at 25%, with only 'categories' and 'startDate' having descriptions. The description adds no parameter semantics beyond the tool's name, failing to explain the purpose of 'categories', 'drivers', or 'worksheetName', leaving most parameters undocumented.

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 specific action ('Generate') and resource ('13-week rolling cash flow forecast') with additional outputs ('confidence intervals and risk analysis'). It distinguishes from siblings like 'analytics_52_week_forecast' by specifying the 13-week duration and from 'cash_flow_forecast' by emphasizing statistical features.

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

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

No explicit guidance on when to use this tool versus alternatives like 'analytics_52_week_forecast' or 'cash_flow_forecast'. The description implies usage for forecasting with uncertainty analysis but lacks context on prerequisites, typical scenarios, 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 are provided, so the description carries the full burden of behavioral disclosure. It mentions 'advanced trend modeling and uncertainty analysis', hinting at computational complexity and probabilistic outputs, but fails to describe critical behaviors such as required permissions, rate limits, output format, error handling, or whether it modifies data. For a complex forecasting tool with zero annotation coverage, this is a significant gap.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It avoids redundancy and wastes no words, making it easy to parse quickly. This is an example of optimal conciseness for a tool description.

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

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

Given the tool's complexity (4 parameters with nested objects, no output schema, and no annotations), the description is incomplete. It lacks parameter explanations, behavioral details, output information, and differentiation from siblings. While concise, it does not provide enough context for the agent to understand how to use the tool effectively in this rich environment.

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 no parameters are documented in the schema. The description does not mention any parameters or their semantics, leaving all 4 parameters (including complex nested objects like 'categories' and 'drivers') unexplained. This forces the agent to infer meaning from schema structure alone, which is insufficient for effective tool 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's purpose: 'Generate 52-week rolling cash flow forecast with advanced trend modeling and uncertainty analysis'. It specifies the verb ('Generate'), resource ('52-week rolling cash flow forecast'), and key features ('advanced trend modeling and uncertainty analysis'). However, it does not explicitly differentiate from its sibling 'analytics_13_week_forecast' or other forecasting tools like 'cash_flow_forecast', which prevents a perfect score.

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. With many sibling tools available (e.g., 'analytics_13_week_forecast', 'analytics_scenario_comparison', 'cash_flow_forecast'), there is no indication of specific use cases, prerequisites, or comparisons. This leaves the agent without direction on tool selection.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions building a model with sensitivity analysis, but lacks details on what the tool actually does (e.g., creates a spreadsheet, generates a report, returns data), permissions required, potential side effects, or output format. This is inadequate for a tool with 9 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?

The description is a single, efficient sentence with no wasted words, clearly front-loading the core action ('Build comprehensive DCF valuation model'). It is appropriately sized for the tool's complexity, earning a high score for 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 tool's complexity (9 parameters, no output schema, no annotations), the description is insufficient. It doesn't explain what the tool outputs (e.g., a file, a calculation result), how sensitivity analysis is performed, or any behavioral traits. This leaves significant gaps for an AI agent to understand and use the tool effectively.

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 high description coverage (89%), documenting most parameters well (e.g., 'discountRate' as WACC). The description adds no additional parameter semantics beyond what the schema provides, but since coverage is high, the baseline score of 3 is appropriate as the schema does the heavy lifting.

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 ('Build') and resource ('comprehensive DCF valuation model with sensitivity analysis'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'analytics_scenario_comparison' or 'analytics_sensitivity_analysis', which might have overlapping functionality, so it doesn't reach the highest score.

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, such as 'analytics_monte_carlo_simulation' or 'calculate_npv', which are related financial modeling tools. There is no mention of prerequisites, context, or exclusions, leaving the agent with minimal usage direction.

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 of behavioral disclosure. It mentions 'automated insights' but fails to describe key traits: whether this is a read-only or mutation operation, what permissions are needed, how results are delivered (e.g., file output, visual display), or any rate limits. For a complex tool with no annotations, this is a significant gap.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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

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

Given the tool's complexity (6 parameters with nested objects, no output schema, no annotations), the description is insufficient. It lacks details on behavioral traits, parameter usage, output format, and differentiation from siblings. For a tool that likely generates a significant output like a dashboard, more context is needed to guide the agent effectively.

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 does not mention any parameters, leaving all semantic meaning to the input schema. With low schema description coverage (17%), most parameters lack documentation in both the schema and description. The description adds no value beyond the schema, but since schema coverage is low, it doesn't compensate adequately, resulting in a baseline 3.

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

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

The description clearly states the tool's purpose: 'Generate comprehensive executive dashboard with automated insights and KPI tracking.' It specifies the verb ('generate') and resource ('executive dashboard'), and distinguishes it from siblings like 'analytics_kpi_dashboard' by emphasizing comprehensiveness and executive focus. However, it doesn't explicitly contrast with all siblings, keeping it at 4 instead of 5.

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. With many sibling tools (e.g., 'analytics_kpi_dashboard', 'cash_flow_forecast'), there is no indication of context, prerequisites, or exclusions. This leaves the agent guessing about appropriate use 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Generate' and 'dashboard,' implying a creation or output operation, but fails to describe critical behaviors such as whether this tool modifies existing data, requires specific permissions, has rate limits, or what the output format looks like (e.g., visual dashboard, report file). For a tool with no annotation coverage, this leaves significant gaps in understanding its operational impact.

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

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

The description is a single, efficient sentence: 'Generate focused KPI performance dashboard with status tracking and trend analysis.' It is front-loaded with the core action and purpose, with no redundant or verbose language. Every word contributes directly to conveying the tool's function, making it appropriately concise and well-structured.

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

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

Given the tool's complexity (2 parameters with nested objects, no annotations, and no output schema), the description is incomplete. It does not address parameter meanings, behavioral traits, output expectations, or differentiation from siblings. For a tool that likely generates a detailed dashboard, the description fails to provide sufficient context for an agent to use it effectively without additional inference or trial-and-error.

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 input schema provides no descriptions for parameters. The tool description does not compensate by explaining what 'kpis' or 'worksheetName' represent, their expected formats, or how they influence the dashboard generation. With 2 parameters (one required, one optional) and complex nested structures in 'kpis', the lack of semantic guidance in the description is a major shortfall.

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: 'Generate focused KPI performance dashboard with status tracking and trend analysis.' It specifies the verb ('Generate') and resource ('KPI performance dashboard'), and distinguishes it from siblings like 'analytics_executive_dashboard' by focusing on KPI-specific metrics. However, it doesn't explicitly differentiate from other analytics tools beyond the KPI focus, preventing a perfect score.

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. With many sibling tools (e.g., 'analytics_executive_dashboard', 'analytics_scenario_comparison'), there is no indication of specific contexts, prerequisites, or exclusions. The agent must infer usage based on the name and description alone, which is insufficient for effective tool selection.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Run' implies execution, the description doesn't mention whether this is a read-only analysis or creates/modifies data, what permissions might be required, whether it's computationally intensive, what the output format is, or any error conditions. For a complex simulation tool with no annotation coverage, this is a significant gap in behavioral context.

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

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

The description is extremely concise - a single sentence that efficiently communicates the core purpose. Every word earns its place: 'Run' (action), 'Monte Carlo simulation' (method), 'for risk analysis and scenario planning' (application). There's no wasted verbiage or redundant 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 complex simulation tool with 6 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns, how results are presented, whether it creates persistent outputs, or what computational resources are required. The description covers only the basic purpose, leaving critical contextual gaps for proper tool selection and invocation.

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

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

Schema description coverage is 67%, so the schema documents most parameters well. The description adds no parameter-specific information beyond what's in the schema - it doesn't explain the relationship between 'formula' and 'variables', provide examples of valid formulas, or clarify distribution parameter usage. With moderate schema coverage, the baseline of 3 is appropriate as the description doesn't compensate for the coverage gap but doesn't contradict the schema either.

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: 'Run Monte Carlo simulation for risk analysis and scenario planning.' It specifies the verb ('Run') and resource ('Monte Carlo simulation'), and distinguishes from many siblings by focusing on simulation rather than forecasting, valuation, or dashboard creation. However, it doesn't explicitly differentiate from 'analytics_scenario_comparison' or 'analytics_sensitivity_analysis' which might also involve scenario 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 provides no guidance on when to use this tool versus alternatives. With numerous sibling tools like 'analytics_scenario_comparison', 'analytics_sensitivity_analysis', and various forecasting tools, there's no indication of when Monte Carlo simulation is preferred over other analytical methods. The description only states what it does, not when it's 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 are provided, so the description carries full burden. It mentions 'probability weighting' which hints at some calculation behavior, but doesn't disclose what the tool actually produces (e.g., comparison metrics, visual output, statistical analysis), whether it modifies data, requires specific permissions, or has any limitations. The behavioral aspects are largely unspecified.

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 - a single sentence that efficiently communicates the core purpose. Every word earns its place, with no redundant information or unnecessary elaboration. It's front-loaded with the essential action and scope.

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 the input schema (nested objects with arrays, multiple required fields) and 0% schema description coverage, the description is inadequate. No output schema exists, so the description should explain what results to expect. For a tool with this level of parameter complexity and no annotations, the single-sentence description leaves too many questions unanswered about behavior, output, and proper 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. It mentions 'scenarios' and 'probability weighting' which aligns with the 'scenarios' array parameter, but doesn't explain the 'worksheetName' parameter at all. The description provides minimal semantic context beyond what can be inferred from parameter names, leaving significant gaps in understanding what data to provide and how it should be structured.

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 'compare' and the resource 'multiple scenarios' with specific types 'Best/Base/Worst case' and mentions 'probability weighting'. It distinguishes this as a comparison tool rather than a creation or analysis tool like its siblings, but doesn't explicitly differentiate from similar comparison tools like analytics_sensitivity_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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or when other tools like analytics_monte_carlo_simulation or analytics_sensitivity_analysis might be more suitable. It simply states what the tool does without usage context.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. While 'perform sensitivity analysis' implies a computational operation, it doesn't describe what the tool actually returns (no output schema), whether it modifies data, requires specific permissions, has rate limits, or what format the results come in. The description is too vague about the actual 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 extremely concise - a single sentence that gets straight to the point without any fluff. Every word serves a purpose, making it front-loaded and efficient. This is appropriate conciseness for a tool description.

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 complex tool with 6 parameters (3 required), no annotations, no output schema, and low schema coverage, the description is inadequate. It doesn't explain what the tool returns, how results are presented, what the 'worksheetName' implies about output format, or provide enough context about the sensitivity analysis methodology. The single sentence leaves too many questions unanswered.

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 only 17% schema description coverage (only 'sensitivityRange' has a description), the description must compensate but fails to do so. It mentions 'variable impact' which hints at the 'variables' parameter, but provides no explanation of what 'formula', 'scenarioName', 'description', or 'worksheetName' mean in context. The description adds minimal value beyond the bare 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's purpose with a specific verb ('perform') and resource ('sensitivity analysis'), and it explains what the analysis does ('understand variable impact on outcomes'). It distinguishes from some siblings like forecasting or valuation tools, but doesn't explicitly differentiate from 'analytics_scenario_comparison' which might have overlapping functionality.

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. With many analytics siblings available (e.g., 'analytics_monte_carlo_simulation', 'analytics_scenario_comparison'), there's no indication of when sensitivity analysis is preferred over other analytical methods or what specific scenarios it's designed for.

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 of behavioral disclosure. It states the tool calculates Macaulay duration, which implies a read-only computation, but doesn't clarify if it's a pure function, what the output format is, error handling, or any performance considerations. For a calculation tool with zero annotation coverage, this leaves significant gaps in understanding its 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 extremely concise—a single sentence with no wasted words. It's front-loaded with the core purpose, making it easy to parse. Every word earns its place, though this conciseness comes at the cost of detail in other dimensions.

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

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

Given the tool's complexity (financial calculation with 2 parameters), lack of annotations, no output schema, and only 50% schema description coverage, the description is inadequate. It doesn't explain the calculation's context, output format, or how to interpret results, leaving the agent with insufficient information to use the tool effectively beyond its basic purpose.

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 description coverage is 50% (only 'cashFlows' has a description). The description doesn't add any parameter details beyond what the schema provides—it doesn't explain what 'cashFlows' or 'yieldRate' represent in the context of Macaulay duration, their units, or valid ranges. With partial schema coverage, the description fails to compensate, resulting in a baseline score.

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

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

The description clearly states the tool's purpose: 'Calculate Macaulay duration for bond'. It specifies the verb ('Calculate') and the resource/calculation type ('Macaulay duration for bond'), making the intent unambiguous. However, it doesn't differentiate from sibling tools like 'calculate_bond_price' or other bond-related calculations, which would require a 5.

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. There are many sibling tools for financial calculations (e.g., 'calculate_bond_price', 'calculate_irr'), but no indication of when Macaulay duration is appropriate, what prerequisites exist, or when other tools 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 are provided, so the description carries the full burden of behavioral disclosure. The description states 'Analyze,' which implies a read-only operation, but it doesn't specify whether this tool performs calculations, returns recommendations, or modifies data. It lacks details on permissions, rate limits, or output format, which are critical for a tool with no annotations.

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

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

The description is a single, efficient sentence with no wasted words. It is front-loaded and appropriately sized for a basic purpose statement, though it could benefit from additional context. The structure is clear but minimal.

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 (2 required parameters, no schema descriptions, no annotations, and no output schema), the description is incomplete. It doesn't explain what the tool returns, how to interpret results, or the role of parameters like 'entityType'. For a financial analysis tool, this lack of context makes it inadequate for effective 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?

The schema description coverage is 0%, meaning parameters are undocumented in the schema. The description does not mention any parameters (e.g., 'expenses' or 'entityType'), nor does it explain their purpose or format. For a tool with 2 required parameters, this is a significant gap, as the description adds no semantic 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 'Analyze allowable business deductions' clearly states the tool's purpose with a specific verb ('Analyze') and resource ('business deductions'). However, it doesn't distinguish this tool from sibling tools like 'calculate_depreciation_deduction' or 'business_tax_summary', which also relate to deductions or business taxes. The purpose is clear but lacks sibling differentiation.

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. There are no explicit instructions, prerequisites, or comparisons to sibling tools (e.g., 'business_tax_summary' or tax-related tools). This leaves the agent without context for tool selection.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Generate' implies a read-only or computational operation, but the description doesn't specify whether this tool requires specific permissions, how it processes data, what the output looks like, or if it has side effects like data storage. For a tool with three required parameters and no annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence with no wasted words, making it easy to parse. It's appropriately sized for a tool with a straightforward name, though it could benefit from more detail given the complexity implied by 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 the tool's complexity (three required parameters, nested objects, no output schema, and no annotations), the description is incomplete. It doesn't explain the output format, behavioral traits, or parameter meanings, leaving significant gaps for an agent to understand how to use it effectively in context with other tax and analytics tools.

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

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

Schema description coverage is 0%, meaning none of the parameters (entityId, taxYear, financialData with revenue and expenses) are documented in the schema. The description mentions 'comprehensive business tax summary', which hints at the purpose but doesn't explain what each parameter means, their formats, or how they influence the summary. This fails to compensate for the lack of schema documentation.

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

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

The description states the tool's purpose as 'Generate comprehensive business tax summary', which includes a verb ('Generate') and resource ('business tax summary'), making it clear what it does at a high level. However, it doesn't distinguish this tool from sibling tools like 'calculate_federal_income_tax', 'calculate_state_taxes', or 'tax_projection_scenarios', leaving ambiguity about its specific scope or output format compared to alternatives.

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 other tax-related tools in the sibling list, such as 'calculate_federal_income_tax' or 'tax_planning_strategies'. It lacks explicit instructions on prerequisites, context, or alternatives, leaving the agent to infer usage based solely on the tool 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but provides no information about computational behavior, error handling, assumptions (e.g., clean price vs. dirty price), or output format. For a financial calculation tool with 5 parameters, this leaves significant behavioral gaps unaddressed.

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 at just 6 words, with zero wasted language. It's front-loaded with the core purpose and uses efficient phrasing. Every word earns its place, making it easy to parse while conveying the essential function.

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

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

For a financial calculation tool with 5 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain the calculation method, output format, assumptions, or typical use context. The combination of incomplete parameter documentation and missing behavioral information creates significant gaps for an agent trying to use this 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 description coverage is 60%, with 3 of 5 parameters having descriptions. The tool description adds minimal value beyond the schema, only mentioning 'yield and terms' generally. It doesn't explain parameter relationships, typical values, or calculation methodology. The baseline is appropriate given moderate schema coverage, but the description doesn't compensate for the 40% coverage gap.

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' and the resource 'bond price', making the purpose immediately understandable. It distinguishes from siblings like 'bond_duration' by focusing on price calculation rather than duration metrics. However, it doesn't explicitly differentiate from other calculation tools like 'calculate_npv' or 'calculate_irr' beyond the bond focus.

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. It doesn't mention sibling tools like 'bond_duration' for related calculations or other financial calculation tools. There's no context about prerequisites, typical use cases, or when this calculation would be appropriate versus other bond analysis methods.

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 of behavioral disclosure. It states it 'calculates' a deduction, implying a read-only operation, but does not specify if it requires authentication, has rate limits, returns specific data formats, or handles errors. For a tool with zero annotation coverage, this is insufficient for safe and effective use.

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

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

The description is a single, efficient sentence with no wasted words, making it highly concise and front-loaded. It directly states the tool's purpose without unnecessary elaboration.

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 tax depreciation calculations, no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavioral traits, parameter meanings, return values, and usage context, making it inadequate for the agent to use the tool effectively.

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 description coverage is 0%, meaning the two parameters (assetId and taxYear) are undocumented in the schema. The description adds no information about what these parameters represent, their expected formats (e.g., string format for assetId, numeric year for taxYear), or constraints, failing to compensate for the low 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 verb 'calculate' and the resource 'tax depreciation deduction for an asset', making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'depreciation_macrs' or 'depreciation_straight_line', which might handle similar calculations but with different methods, so it misses full sibling differentiation.

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, such as other depreciation methods or tax-related tools in the sibling list. It lacks context on prerequisites, exclusions, or specific scenarios, leaving the agent without usage direction.

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 of behavioral disclosure. It states the calculation is based on 'taxable income and filing status,' but doesn't reveal whether this uses current tax laws, includes credits/deductions, handles edge cases, or provides error handling. For a tax calculation tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It's appropriately sized for a straightforward calculation tool, with zero wasted text or redundancy.

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

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

Given the complexity of tax calculations, no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on tax year, algorithm assumptions, return format, error conditions, or dependencies. For a tool with 2 parameters and no structured support, this leaves significant gaps for an AI agent to use it 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 schema provides no parameter descriptions. The description mentions 'taxable income and filing status,' which aligns with the two parameters, but adds minimal semantics beyond naming them. It doesn't explain units for taxable income, the meaning of filing statuses, or default behaviors. With low schema coverage, the description only partially compensates, warranting a baseline score.

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

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

The description clearly states the tool's purpose: 'Calculate federal income tax based on taxable income and filing status.' It specifies the verb ('calculate'), resource ('federal income tax'), and key inputs. However, it doesn't explicitly differentiate from sibling tools like 'calculate_state_taxes' or 'calculate_self_employment_tax' beyond the 'federal' qualifier, which is why it's a 4 rather than a 5.

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. It doesn't mention when to choose this over 'calculate_state_taxes' or 'tax_projection_scenarios', nor does it specify prerequisites like tax year, applicable deductions, or jurisdiction. This lack of contextual guidance limits its utility for an AI agent.

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 of behavioral disclosure. It states 'calculate' but doesn't clarify whether this is a read-only computation or if it modifies data, what permissions are needed, or what the output format looks like. For a tool with no annotations, this leaves critical behavioral traits unspecified.

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

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

The description is a single, efficient sentence with no wasted words. It's front-loaded and easy to parse, though it could be more informative. The brevity is appropriate but borders on under-specification given the tool's complexity.

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

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

Given the tool's complexity (2 parameters with nested objects, no output schema, and no annotations), the description is inadequate. It lacks details on behavioral traits, parameter usage, output format, and differentiation from siblings. For a calculation tool with financial data, this leaves too many gaps for effective agent 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 description coverage is 50%, with one parameter ('values') having a generic description. The tool description adds no parameter-specific information beyond the schema, such as explaining the structure of 'values' or providing examples. Since schema coverage is moderate, the baseline is 3, but the description doesn't compensate for the coverage gap.

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 'Calculate comprehensive financial ratios' clearly states the verb ('calculate') and resource ('financial ratios'), but it's vague about scope and differentiation. It doesn't specify what makes the ratios 'comprehensive' or how this tool differs from sibling tools like 'financial_ratios_analysis' or 'excel_create_financial_ratios', leaving ambiguity about its specific purpose.

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. With many sibling tools (e.g., 'financial_ratios_analysis', 'liquidity_analysis', 'excel_create_financial_ratios'), there's no indication of context, prerequisites, or exclusions. This omission makes it difficult for an agent to choose appropriately among similar tools.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool calculates without mentioning how it behaves—no information on return format, error handling (e.g., for non-converging cash flows), computational limits, or assumptions (e.g., reinvestment rate). This leaves the agent with insufficient operational context.

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

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

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable. This brevity is effective for a straightforward tool, though it may trade off completeness for 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 tool's complexity (financial calculation with potential for nuanced behavior) and lack of annotations or output schema, the description is incomplete. It doesn't explain what IRR is, how results are returned, or edge cases, leaving the agent under-informed. While the schema covers parameters, overall context is inadequate for reliable 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?

The input schema has 100% description coverage, with the 'cashFlows' parameter documented as 'Cash flows including initial investment'. The description adds no additional parameter semantics beyond this, such as examples or constraints (e.g., negative initial investment). Given the high schema coverage, the baseline score of 3 is appropriate, as the schema handles the heavy lifting.

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 'Calculate Internal Rate of Return' clearly states the verb (calculate) and resource (IRR), providing a basic understanding of the tool's function. However, it doesn't differentiate this tool from its sibling 'calculate_mirr' (Modified IRR) or other financial calculation tools like 'calculate_npv', leaving the purpose somewhat vague in 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios where IRR is appropriate (e.g., investment analysis), contrast it with MIRR or NPV, or specify prerequisites like cash flow ordering. This absence of usage context is a significant 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 of behavioral disclosure. While 'Calculate' implies a computational operation, it doesn't specify whether this is a read-only calculation, what format the output takes (e.g., percentage, decimal), error conditions, or performance characteristics. For a financial calculation tool with zero annotation coverage, this is a significant gap.

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

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

The description is a single, efficient phrase with zero waste. It's appropriately sized for a straightforward calculation tool and front-loads the core purpose without unnecessary elaboration.

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 financial calculations, no annotations, no output schema, and moderate schema coverage, the description is incomplete. It lacks crucial context like output format, error handling, and differentiation from similar tools, making it inadequate for reliable agent use 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 67% (2 out of 3 parameters have descriptions in the schema). The description adds no parameter information beyond what's in the schema. Since schema coverage is moderate, the baseline is 3—the description doesn't compensate for the partial coverage but doesn't make it worse either.

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 'Calculate Modified Internal Rate of Return' clearly states the verb ('Calculate') and the specific financial metric ('Modified Internal Rate of Return'), which is more specific than just 'MIRR'. However, it doesn't differentiate from sibling tools like 'calculate_irr' or 'calculate_npv', leaving ambiguity about when to choose this specific IRR variant over others.

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. With siblings like 'calculate_irr' and 'calculate_npv' available, there's no mention of MIRR's specific use cases (e.g., addressing multiple IRR issues, different reinvestment assumptions) or prerequisites. This leaves the agent without context for tool selection.

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

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

No annotations are provided, so the description carries the full burden. It states the tool calculates NPV but doesn't disclose behavioral aspects like whether it's a read-only operation, what format the result is in, error handling, or any computational assumptions. For a financial calculation tool with zero annotation coverage, this leaves significant gaps.

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

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

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a straightforward calculation tool.

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 financial calculations, no annotations, no output schema, and low parameter documentation (33% coverage), the description is incomplete. It doesn't explain what the tool returns, how cash flows are interpreted (e.g., timing), or any assumptions, making it inadequate for reliable 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 description coverage is 33% (only 'rate' has a description), with 'cashFlows' and 'initialInvestment' undocumented. The description adds no parameter semantics beyond the schema, failing to compensate for the low coverage. However, the schema provides basic structure, so it meets the minimum viable baseline.

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

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

The description clearly states the tool's purpose with a specific verb ('Calculate') and resource ('Net Present Value of cash flows'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'calculate_irr', 'calculate_mirr', or 'present_value', which are related 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 provides no guidance on when to use this tool versus alternatives. With many sibling tools for financial calculations (e.g., 'calculate_irr', 'present_value', 'analytics_dcf_valuation'), there's no indication of when NPV is preferred or what distinguishes it from other valuation methods.

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 of behavioral disclosure. It states 'calculate' which implies a read-only computation, but doesn't clarify if this is a simulation, requires specific data inputs beyond wages/year, or has any side effects (e.g., saving results). For a tool with zero annotation coverage, this is insufficient.

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

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

The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.

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 tax calculations, no annotations, 0% schema coverage, and no output schema, the description is inadequate. It doesn't explain what the calculation includes (e.g., FICA, Medicare), how results are returned, or any assumptions, leaving significant gaps for an agent 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 input schema has 0% description coverage, so parameters 'wages' and 'year' are undocumented in the schema. The description adds no information about what these parameters mean (e.g., wages as gross pay, year as tax year), their units, or constraints, failing to compensate for the schema gap.

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' and the resource 'payroll taxes for employer and employee', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'calculate_federal_income_tax' or 'calculate_state_taxes', which are related but distinct tax 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., for payroll processing), or comparisons to sibling tools like 'calculate_self_employment_tax', 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 are provided, so the description carries the full burden of behavioral disclosure. It states the tool calculates tax but doesn't reveal critical details: whether it's a read-only calculation or has side effects (e.g., saving results), if it requires authentication, rate limits, error handling, or output format. For a financial tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is extremely concise—a single sentence with no wasted words. It front-loads the core purpose ('Calculate self-employment tax') and adds clarifying detail ('Social Security and Medicare') efficiently. Every element earns its place, making it easy to parse quickly.

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 tax calculations and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., tax amount, breakdown by Social Security/Medicare), assumptions (e.g., current tax year, rates), or limitations. For a tool with no structured output and behavioral gaps, this leaves 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?

The input schema has 100% description coverage, with one parameter ('netEarnings') clearly documented. The description doesn't add any parameter-specific details beyond what the schema provides (e.g., tax year, deductions, or thresholds). Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to.

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: 'Calculate self-employment tax (Social Security and Medicare)'. It specifies the verb ('calculate') and resource ('self-employment tax'), making it unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'calculate_federal_income_tax' or 'calculate_payroll_taxes', which are related but distinct tax 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., for self-employed individuals), contrast it with other tax calculation tools in the list (e.g., 'calculate_federal_income_tax'), or specify scenarios where it's applicable. Usage is implied but not articulated.

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 of behavioral disclosure. It states the tool calculates taxes but doesn't mention whether it's a read-only operation, if it requires authentication, rate limits, error handling, or what the output looks like (e.g., tax amount, breakdown). For a calculation tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence with zero waste: 'Calculate state income tax for supported states'. It is front-loaded and appropriately sized, conveying the core purpose without unnecessary detail. Every word earns its place.

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

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

Given the complexity of tax calculation, lack of annotations, no output schema, and low schema description coverage (33%), the description is incomplete. It doesn't address behavioral aspects, output format, error cases, or usage context, leaving the agent with insufficient information to use the tool effectively beyond basic parameter passing.

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 adds minimal parameter semantics beyond the schema. It implies 'state' and 'taxableIncome' are key inputs but doesn't explain their roles or constraints. With schema description coverage at 33% (only 'state' has a description), the description doesn't compensate for the undocumented 'taxableIncome' and 'filingStatus' parameters. However, the schema's enums and default provide some structure, keeping it at baseline.

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

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

The description clearly states the tool's purpose: 'Calculate state income tax for supported states'. It specifies the verb ('calculate'), resource ('state income tax'), and scope ('supported states'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'calculate_federal_income_tax' or 'calculate_payroll_taxes', though the 'state' focus is implied.

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. It mentions 'supported states' but doesn't specify which states are supported (though the schema's enum provides this), nor does it explain prerequisites, limitations, or how it differs from other tax calculation tools in the sibling list. Usage is implied by the name and parameters 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 carries the full burden of behavioral disclosure. It only states the calculation purpose without detailing behavioral traits such as whether it's a read-only operation, if it requires specific inputs or permissions, what the output format might be, or any error handling. This is inadequate for a tool with 5 required 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?

The description is extremely concise with a single phrase, 'Calculate Weighted Average Cost of Capital,' which is front-loaded and wastes no words. However, this conciseness comes at the cost of under-specification, but based solely on structure and brevity, it earns full marks for being tightly written.

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 a financial calculation tool with 5 required parameters, no annotations, and no output schema, the description is severely incomplete. It does not provide enough context for an agent to understand how to invoke the tool correctly, what the inputs mean, or what to expect as a result, making it inadequate for practical 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?

The schema description coverage is 0%, meaning none of the 5 parameters (equityValue, debtValue, costOfEquity, costOfDebt, taxRate) are documented in the schema. The description does not add any meaning beyond the tool name, failing to explain what these parameters represent, their units, or how they are used in the WACC calculation, leaving them entirely undocumented.

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 'Calculate Weighted Average Cost of Capital' restates the tool name (calculate_wacc) with minimal elaboration, making it tautological. It specifies the financial metric (WACC) but lacks a clear verb-resource combination or differentiation from sibling tools like analytics_dcf_valuation or calculate_financial_ratios, which are also financial calculation tools.

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

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention context, prerequisites, or exclusions, and it fails to reference sibling tools (e.g., analytics_scenario_comparison or calculate_npv) that might be relevant for related financial analyses, leaving the agent without usage direction.

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 only states what the tool does ('calculate'), with no information about permissions, rate limits, side effects, output format, or error handling. For a calculation tool with zero annotation coverage, this is inadequate.

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

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

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple calculation tool and front-loads the key information ('Calculate expected return').

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, 0% schema coverage, no output schema, and 3 required parameters, the description is incomplete. It names the tool's function but lacks details on behavior, parameters, and output, making it insufficient for an agent to use the tool effectively without 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 description coverage is 0%, so parameters 'riskFreeRate', 'beta', and 'marketReturn' are undocumented in the schema. The description adds no parameter information beyond naming the CAPM model, which implies these parameters but doesn't explain their meaning, units, or valid ranges. It partially compensates 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 'Calculate expected return using CAPM model' states the verb ('calculate') and resource ('expected return'), but is vague about scope and specifics. It doesn't distinguish from siblings like 'calculate_wacc' or 'calculate_irr' which are also financial calculation tools. The purpose is understandable but lacks differentiation.

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. With many sibling tools for financial calculations (e.g., 'calculate_wacc', 'calculate_irr', 'analytics_scenario_comparison'), the description offers no context about appropriate use cases, prerequisites, or comparisons to other tools.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions analysis and calculation but doesn't specify whether this is a read-only operation, what data sources it uses, whether it performs destructive changes, or what the output format looks like. For a financial analysis tool with zero annotation coverage, this leaves significant behavioral gaps.

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 perfectly concise with just two key actions ('analyze' and 'calculate') and their objects ('cash burn rate' and 'runway'). Every word earns its place, and there's no unnecessary elaboration or redundancy.

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

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

For a financial analysis tool with no annotations, no output schema, and incomplete parameter documentation, the description is inadequate. It doesn't explain what data the analysis is based on, how results are presented, or what assumptions are made. Given the complexity of financial modeling, this leaves too many contextual 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?

The description mentions analyzing cash burn rate and calculating runway but doesn't explain how the 'monthsBack' parameter influences this analysis. With 0% schema description coverage and only one parameter, the description adds minimal value beyond what's implied by the tool name. The baseline is appropriate given the single 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's purpose with specific verbs ('analyze' and 'calculate') and resources ('cash burn rate' and 'runway'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'cash_flow_forecast' or 'cash_flow_at_risk', which prevents a perfect score.

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. With many sibling tools in the analytics and cash flow categories, there's no indication of specific scenarios, prerequisites, or comparisons to tools like 'cash_flow_forecast' or 'analytics_scenario_comparison'.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the calculation action without details on data sources, computational methods, output format, or any behavioral traits like performance or limitations. This is inadequate for a tool that likely involves complex financial modeling.

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, direct sentence with no wasted words, making it highly concise. It is front-loaded with the core action, though this brevity contributes to gaps in other dimensions.

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 financial risk metrics, no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on inputs, outputs, behavior, and usage context, making it insufficient for effective tool invocation in a server with many analytical siblings.

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 one parameter 'confidenceLevel' with a default and range, but schema description coverage is 0%, meaning no descriptions in the schema. The tool description adds no parameter information, failing to explain what 'confidenceLevel' means in the context of CFaR or how it affects the calculation, leaving semantics unclear.

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

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

The description states the tool calculates Cash Flow at Risk (CFaR), which is a specific financial metric, providing a clear verb ('calculate') and resource ('CFaR'). However, it does not differentiate from siblings like 'cash_flow_forecast' or 'analytics_monte_carlo_simulation', which might involve similar risk or cash flow analyses, leaving purpose somewhat vague in 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 provides no guidance on when to use this tool versus alternatives. With many sibling tools related to analytics, cash flow, and risk (e.g., 'analytics_monte_carlo_simulation', 'cash_flow_forecast'), there is no indication of context, prerequisites, or exclusions, making it misleading for selection.

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

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions 'scenario analysis' but doesn't disclose whether this is a read-only calculation, a destructive mutation, authentication requirements, rate limits, or output format. For a forecasting tool with zero annotation coverage, this is inadequate.

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

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

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a tool with two parameters and gets straight to the point without unnecessary elaboration.

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 forecasting tool with 2 parameters (including a nested object), 0% schema coverage, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, how scenarios affect results, or provide enough context for reliable agent 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 description coverage is 0%, so the schema provides no parameter documentation. The description mentions 'scenario analysis' which hints at the 'scenarios' parameter, but doesn't explain 'monthsAhead' or the structure/meaning of scenario multipliers. It adds minimal value beyond what's inferable from 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 'Forecast future cash flows with scenario analysis' clearly states the verb ('forecast') and resource ('future cash flows'), and specifies scenario analysis as a key feature. It distinguishes from generic cash flow tools but doesn't explicitly differentiate from sibling tools like 'analytics_scenario_comparison' or 'cash_flow_at_risk'.

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 is provided. The description doesn't mention prerequisites, appropriate contexts, or exclusions, leaving the agent to infer usage from the tool name alone among many financial analysis 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 are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('Generate cash flow statement') without any information on permissions required, data sources, output format, error handling, or rate limits. For a tool that likely involves financial data processing, this lack of transparency is a significant gap.

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

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

The description is extremely concise with a single sentence ('Generate cash flow statement for specified period'). It is front-loaded and wastes no words, making it easy to parse quickly. Every word contributes directly to the tool's purpose, earning its place efficiently.

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 financial reporting tools, no annotations, no output schema, and low parameter semantics coverage, the description is incomplete. It doesn't address what the cash flow statement includes (e.g., operating, investing, financing activities), how results are returned, or any prerequisites. For a tool in a server with many analytics siblings, more context is needed to guide effective 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?

The input schema has 2 parameters (startDate and endDate) with 0% schema description coverage, meaning the schema provides no descriptions for these parameters. The description adds minimal value by implying a 'specified period' but doesn't explain what the period represents (e.g., fiscal year, quarter), date format expectations, or validation rules. It partially compensates but leaves key semantics unclear.

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

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

The description states the tool's purpose ('Generate cash flow statement') and specifies the resource ('for specified period'), which is clear but somewhat vague. It doesn't distinguish this tool from sibling tools like 'cash_flow_forecast' or 'cash_flow_at_risk', which also deal with cash flow analysis. The description is functional but lacks specificity about what makes this tool unique.

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

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to cash flow (e.g., 'cash_flow_forecast', 'cash_flow_at_risk'), there's no indication of whether this is for historical reporting, forecasting, or risk analysis. The phrase 'for specified period' implies a time-based query but doesn't clarify 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 are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Generate' which implies a creation or computation action, but doesn't disclose whether this tool requires specific data inputs, permissions, or how it handles errors. There's no information on output format (e.g., structured data, file generation) or side effects, which is a significant gap for a tool with parameters.

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 and front-loaded with a single sentence that states the core function. There's no unnecessary verbiage, and it efficiently communicates the basic intent. However, it could be more structured by including key details, but as-is, it avoids waste.

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 (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what a 'comparative income statement' entails, how periods are defined, or what the output looks like. For a tool that likely generates financial reports, more context on behavior, output, and usage is needed to be adequately helpful.

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 description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'multiple periods' which loosely relates to the 'periods' parameter, but doesn't explain the 'outputToExcel' or 'filePath' parameters at all. The description adds minimal value beyond what's implied by the tool name, failing to clarify parameter purposes or usage.

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

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

The description states the tool's purpose ('Generate comparative income statement for multiple periods'), which is clear but vague. It specifies the resource (income statement) and scope (comparative, multiple periods), but doesn't distinguish it from sibling tools like 'generate_income_statement' or other analytics tools. The purpose is understandable but lacks specificity about what makes this tool unique.

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

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools (e.g., 'generate_income_statement', 'analytics_scenario_comparison'), there's no indication of prerequisites, context, or comparisons. It doesn't specify if this is for historical analysis, forecasting, or other use cases, leaving the agent to guess.

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 of behavioral disclosure. It mentions 'full compliance documentation and audit trail,' hinting at output behavior, but doesn't describe critical traits like whether this is a read-only analysis or a write operation that creates records, what permissions are needed, error handling, or rate limits. For a complex financial compliance tool with zero annotation coverage, this is inadequate.

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

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

The description is a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words and gets straight to the point, though it could be slightly more structured by separating compliance aspects from processing details.

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

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

Given the tool's complexity (involving nested objects for contracts, performance obligations, and payment terms), lack of annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, how errors are handled, or the scope of 'process' (e.g., calculation vs. reporting). For a high-stakes compliance tool, 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 description adds no parameter-specific information beyond what the input schema provides. With a schema description coverage of 33% (low), the description doesn't compensate by explaining the semantics of 'contracts', 'asOfDate', or 'worksheetName'. However, since there are only 3 parameters and the schema covers them partially, the baseline is met but not exceeded.

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: 'Process revenue recognition under ASC 606 with full compliance documentation and audit trail.' It specifies the verb ('process'), resource ('revenue recognition'), and compliance context. However, it doesn't explicitly differentiate from sibling tools like 'compliance_audit_preparation' or 'compliance_sox_controls_test', which are also compliance-related.

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. It mentions 'ASC 606' as a context, but doesn't specify prerequisites, when-not-to-use scenarios, or compare it to sibling compliance tools. This leaves the agent without clear usage direction.

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 of behavioral disclosure. It states the tool generates a package, implying a write or creation operation, but doesn't specify what 'comprehensive' entails, whether it modifies existing data, requires specific permissions, or details output format. For a tool with 8 parameters and no annotations, this lack of behavioral context is a significant gap.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand quickly. There's no wasted verbiage, earning a high score for 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 tool's complexity (8 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain what the generated package includes, how it's delivered, or any behavioral aspects like data handling or error conditions. For a tool that likely produces significant output, more context is needed to guide effective 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?

The description adds no parameter-specific information beyond what the input schema provides. With a schema description coverage of 88%, the schema already documents most parameters well, including enums and descriptions. The baseline score of 3 is appropriate since the schema does the heavy lifting, but the description doesn't compensate for the remaining 12% gap or add any extra semantic 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: 'Generate comprehensive audit preparation package with all compliance documentation.' It specifies the verb ('generate') and resource ('audit preparation package'), making the action explicit. However, it doesn't differentiate from sibling tools like 'compliance_sox_controls_test' or 'compliance_asc606_revenue_recognition', which are also compliance-related, so it misses full sibling distinction.

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. It doesn't mention any prerequisites, exclusions, or compare it to sibling tools such as 'compliance_sox_controls_test' or other analytics tools. Without this context, users may struggle to select the appropriate tool for their needs.

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. While 'Test' implies an evaluation operation, the description doesn't specify whether this is a read-only analysis or creates test records, what permissions are required, whether it modifies existing data, what the output format is, or any rate limits. It mentions 'deficiency tracking' but doesn't explain how deficiencies are handled.

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

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

The description is a single, efficient sentence that gets straight to the point. It's appropriately sized for a tool description, though it could benefit from being slightly more specific about the tool's scope and output.

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 complex tool with 3 parameters (including nested arrays), 0% schema description coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain the tool's purpose in sufficient detail, doesn't describe parameters or their relationships, and provides no information about what the tool returns or how results are presented.

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 for undocumented parameters. However, the description provides no information about the three parameters (controls, testParameters, worksheetName) or their relationships. It doesn't explain that controls need to be defined with specific properties or that test parameters must be provided for testing.

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 ('Test') and resource ('SOX controls') with additional context about 'detailed testing procedures and deficiency tracking'. It distinguishes this tool from general compliance tools by specifying SOX controls, though it doesn't explicitly differentiate from the sibling 'compliance_audit_preparation' tool.

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. The description doesn't mention prerequisites, timing considerations, or when to choose this over other compliance or testing tools. It simply states what the tool does without contextual usage information.

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

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

No annotations are provided, so the description carries the full burden. It mentions 'Create' but doesn't disclose behavioral traits such as file system impact (e.g., overwriting existing files), permissions needed, error handling, or output format. For a tool that creates files, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.

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, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how parameters interact, or behavioral details like file creation effects, making it inadequate for a tool with two parameters that likely modifies the file system.

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 schema provides no parameter descriptions. The description mentions 'budget vs actual Excel template' but doesn't explain what 'categories' or 'filePath' parameters mean or how they affect the output. It adds minimal semantic value beyond the schema's structure.

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 ('Create') and resource ('budget vs actual Excel template'), making the tool's purpose evident. However, it doesn't differentiate from sibling tools like 'create_cash_flow_template' or 'expense_budget_vs_actual', which might have overlapping functionality in budget/actual analysis contexts.

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. With siblings like 'create_cash_flow_template' and 'expense_budget_vs_actual', the description lacks context on specific use cases, prerequisites, or exclusions, leaving the agent to infer usage.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool creates an Excel template but does not mention any behavioral traits such as file system interactions (e.g., overwriting existing files), permissions required, error handling, or output format. This leaves significant gaps for a tool that likely writes to a file system.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized, making it easy to parse quickly.

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 creating a file-based template (2 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavior, parameter meanings, output expectations, and how it differs from similar tools, making it inadequate for informed tool selection and invocation.

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

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

Schema description coverage is 0%, meaning the input schema provides no descriptions for parameters. The tool description does not add any semantic information about the parameters (e.g., what 'months' represents or the format/purpose of 'filePath'), failing to compensate for the lack of schema documentation.

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

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

The description clearly states the action ('Create') and the resource ('cash flow projection Excel template'), making the purpose specific and understandable. However, it does not differentiate this tool from sibling tools like 'create_budget_template' or 'excel_create_cash_flow_projection', which limits its score to 4 instead of 5.

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. With many sibling tools related to Excel creation and cash flow analysis (e.g., 'excel_create_cash_flow_projection', 'create_budget_template'), there is no indication of context, prerequisites, or exclusions, leaving the agent without usage direction.

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 of behavioral disclosure. It states 'Create' which implies a write operation, but doesn't specify file system interactions, permissions needed, whether it overwrites existing files, or error handling. For a tool that likely writes to a file path, this is insufficient behavioral detail.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for what it communicates, though it could benefit from additional context.

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

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

For a tool with 2 parameters (including a complex nested object), 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain what the analysis contains, how the template is structured, what happens when the file is created, or any behavioral aspects. The description fails to compensate for the lack of structured 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 schema provides no parameter documentation. The description mentions 'rental property analysis' which hints at the propertyData parameter content, but doesn't explain what data fields are expected, their units, or the filePath parameter's purpose. It adds minimal semantic value beyond the tool name.

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 action ('Create') and the output ('rental property analysis Excel template'), which is specific and distinguishes it from general Excel tools. However, it doesn't explicitly differentiate from sibling tools like 'create_budget_template' or 'create_cash_flow_template' beyond the domain 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?

No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, when it's appropriate compared to other rental or analysis tools, or any exclusions. It's a standalone statement with no usage context.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It states it 'calculates' a schedule but doesn't describe what the output looks like (e.g., period-by-period table, summary values), whether it's a read-only calculation or has side effects, or any performance considerations. For a calculation tool with zero annotation coverage, this represents a significant transparency gap.

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

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

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized for a calculation tool and front-loads the essential information, making it easy to parse quickly.

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 financial calculation tool with 4 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain the output format, doesn't provide context about when to use declining balance versus other depreciation methods, and doesn't clarify parameter semantics beyond the minimal schema coverage. The agent would struggle to use this tool effectively without additional 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?

The description mentions 'declining balance' but doesn't explain what the parameters represent beyond what's minimally inferred from their names. With only 25% schema description coverage (only the 'rate' parameter has a description), the description doesn't compensate for the undocumented parameters (cost, salvageValue, usefulLife). It doesn't clarify units, valid ranges, or relationships between parameters, providing marginal value over the bare 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 verb 'calculate' and the resource 'declining balance depreciation schedule', making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from its sibling depreciation tools (MACRS, straight-line, sum-of-years, units production) beyond naming the method, which would require additional context about when to choose declining balance over other methods.

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 alternative depreciation calculation methods available in the sibling tools list. There's no mention of prerequisites, typical use cases, or comparison with other depreciation approaches, leaving the agent with insufficient context for appropriate tool selection.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Calculate' implies a read-only computation, but the description doesn't specify whether this creates persistent data, requires authentication, has rate limits, or what format the schedule output takes. For a calculation tool with no annotation coverage, this leaves significant behavioral questions unanswered.

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

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

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a straightforward calculation tool and front-loads the essential information. Every word earns its place in conveying the core functionality.

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

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

For a calculation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the output looks like (e.g., annual schedule, monthly breakdown, percentages vs. dollar amounts), doesn't mention any assumptions or limitations of MACRS calculations, and doesn't provide context about when this specific depreciation method is applicable versus alternatives.

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 'MACRS depreciation schedule' which implies both cost and recovery period parameters, but adds no specific semantic information beyond what the schema provides. With 50% schema description coverage (only recoveryPeriod has a description), the description doesn't compensate for the undocumented 'cost' parameter. The baseline is 3 since the schema covers half the parameters adequately.

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') and resource ('MACRS depreciation schedule'), making the purpose specific and understandable. It distinguishes from other depreciation methods like 'depreciation_straight_line' or 'depreciation_declining_balance' by specifying MACRS, but doesn't explicitly differentiate from 'calculate_depreciation_deduction' which might be a sibling tool with overlapping functionality.

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. With multiple depreciation-related tools in the sibling list (depreciation_straight_line, depreciation_declining_balance, depreciation_sum_of_years, depreciation_units_production, calculate_depreciation_deduction), there's no indication of when MACRS is appropriate versus other methods or what distinguishes this calculation from the generic 'calculate_depreciation_deduction' tool.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool calculates a schedule, implying a read-only operation, but doesn't clarify if it's a pure computation, whether it requires specific inputs beyond the schema, or what the output format looks like (e.g., annual/monthly breakdown). For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a straightforward calculation tool, making it easy for an agent to parse quickly.

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

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

Given the tool's moderate complexity (3 required parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on output format, error conditions, or usage context. Without annotations or output schema, the agent must rely on the schema alone for execution, which is workable but not ideal.

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 adds no parameter-specific information beyond what the input schema provides. With schema description coverage at 33% (only 'usefulLife' has a description), the description doesn't compensate by explaining 'cost' or 'salvageValue'. However, the baseline is 3 since the schema covers all parameters structurally, even if descriptions are 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 action ('Calculate') and the specific resource ('straight-line depreciation schedule'), making the tool's purpose immediately understandable. It distinguishes from sibling tools like 'depreciation_declining_balance' and 'depreciation_macrs' by specifying the straight-line method, though it doesn't explicitly contrast with them in the description text.

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 alternative depreciation methods (e.g., declining balance, MACRS, sum-of-years, units of production) that are present among sibling tools. It lacks any context about typical use cases, prerequisites, or comparisons to other tools, leaving the agent to infer usage scenarios.

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 of behavioral disclosure. It only states what the tool calculates, without mentioning whether it's a read-only operation, if it has side effects, what the output format is, or any performance considerations. For a calculation tool with zero annotation coverage, this is inadequate.

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

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

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and uses precise terminology. Every word earns its place, making it easy to parse quickly.

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 annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how errors are handled, or provide context about the depreciation method. For a financial calculation tool with three parameters, more detail is needed to be fully usable.

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, so parameters 'cost', 'salvageValue', and 'usefulLife' are undocumented in the schema. The description adds no information about what these parameters mean, their units, valid ranges, or how they relate to the calculation. It fails to compensate for the schema's lack of documentation.

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

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

The description clearly states the tool's purpose with a specific verb ('calculate') and resource ('sum-of-years-digits depreciation schedule'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling depreciation tools like 'depreciation_declining_balance' or 'depreciation_straight_line', which would require mentioning the specific calculation method as a distinguishing factor.

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. With multiple depreciation methods available as siblings (e.g., 'depreciation_declining_balance', 'depreciation_macrs'), there's no indication of scenarios where sum-of-years-digits is preferred, nor any 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool performs a calculation but doesn't mention whether it's read-only, if it modifies data, what the output format is, or any error conditions. For a calculation tool with 4 required parameters, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized for a calculation tool, though its brevity contributes to the gaps in other dimensions.

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 a depreciation calculation with 4 required parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain the calculation method, parameter relationships, expected output format, or error handling, leaving the agent with insufficient information to use the tool effectively.

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 none of the 4 parameters have descriptions in the schema. The tool description doesn't explain what 'cost', 'salvageValue', 'totalUnits', or 'unitsPerPeriod' represent, their units, or how they relate to the units of production method. The description fails to compensate for the complete lack of schema documentation.

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

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

The description states the tool's purpose as 'Calculate units of production depreciation', which is a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'depreciation_declining_balance', 'depreciation_macrs', 'depreciation_straight_line', or 'depreciation_sum_of_years', leaving ambiguity about when to choose this specific depreciation method over others.

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 alternative depreciation methods available in the sibling tools. There's no mention of prerequisites, typical use cases, or comparison with other depreciation calculations, leaving the agent without context for selection.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does ('calculate'), but doesn't disclose any behavioral traits such as whether it's a pure computation (likely read-only), what format the output might be in, error conditions, or computational limits. For a calculation tool with zero annotation coverage, this is a significant gap.

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 and front-loaded with a single clear sentence: 'Calculate effective annual rate from nominal rate'. Every word earns its place, with zero wasted text or unnecessary elaboration. It efficiently communicates the core purpose without any structural issues.

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

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

Given that this is a simple calculation tool with 2 parameters and 100% schema coverage, the description is minimally adequate. However, with no annotations and no output schema, the description doesn't provide enough context about what the tool returns or its behavioral characteristics. For a calculation tool, users would benefit from knowing the output format or units, but the description doesn't address this.

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

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

Schema description coverage is 100%, so the input schema already fully documents both parameters ('nominalRate' and 'compoundingPeriods') with clear descriptions. The tool description doesn't add any parameter-specific information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

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: 'Calculate effective annual rate from nominal rate'. It specifies the verb ('calculate') and the resource ('effective annual rate'), and distinguishes it from siblings by focusing on a specific financial calculation. However, it doesn't explicitly differentiate from similar tools like 'calculate_irr' or 'capm_expected_return' which are also financial calculation 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for application, or comparison to sibling tools like 'calculate_irr' or 'future_value'. The agent must infer usage solely from the tool 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 full burden of behavioral disclosure. While 'calculate' suggests a read-only operation, the description doesn't clarify whether this is a simulation, requires specific permissions, has rate limits, or what the output format looks like. For a financial calculation tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a calculation tool and front-loads the core purpose without unnecessary elaboration.

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 financial calculation tool with 3 parameters, 0% schema description coverage, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain the calculation methodology, output format, or provide enough context for an agent to understand when and how to use this tool effectively compared to other tax calculations.

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 (no parameter descriptions in the schema), the description provides no information about the three parameters (annualIncome, filingStatus, selfEmployed). The description doesn't explain what these parameters mean, how they affect the calculation, or provide any context beyond what's in the bare schema. This fails to compensate for the schema's lack of documentation.

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

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

The description 'Calculate estimated quarterly tax payments' clearly states the verb ('calculate') and resource ('estimated quarterly tax payments'), making the tool's purpose immediately understandable. However, it doesn't explicitly differentiate itself from sibling tools like 'calculate_federal_income_tax' or 'calculate_self_employment_tax', which are also tax-related 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 provides no guidance on when to use this tool versus alternatives. With multiple tax calculation tools in the sibling list (e.g., 'calculate_federal_income_tax', 'calculate_self_employment_tax', 'calculate_state_taxes'), there's no indication of when estimated quarterly taxes are appropriate versus annual calculations or other tax types.

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 mentions 'documentation and validation' but doesn't explain what these entail (e.g., where documentation is placed, what validation checks occur, whether the tool modifies existing content, or what happens on errors). For a tool that modifies Excel files, this lack of detail is significant.

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

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

The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place by specifying the action, target, and key features without redundancy or unnecessary elaboration.

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 5 parameters, no annotations, no output schema, and complex financial operations, the description is inadequate. It doesn't cover behavioral aspects like side effects, error handling, or output format, nor does it detail parameter interactions or formula-specific behaviors, leaving significant gaps for an AI agent.

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

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

Schema description coverage is 60%, and the description adds minimal parameter semantics beyond the schema. It implies 'financial formula' relates to 'formulaType' and 'parameters', and 'documentation' relates to 'addDocumentation', but doesn't explain parameter formats, formula-specific requirements, or how 'complete documentation' is implemented. The description compensates somewhat but not fully for the coverage gap.

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 action ('Add a financial formula') and the resource ('to a cell'), and specifies additional features ('with complete documentation and validation'). It distinguishes itself from other Excel tools by focusing on formula insertion with documentation, but doesn't explicitly differentiate from all sibling tools like 'excel_create_formula_reference' or 'excel_enforce_formula_rule'.

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. It doesn't mention prerequisites (e.g., needing an open workbook), exclusions, or comparisons to sibling tools like 'excel_create_financial_ratios' or 'excel_write_calculation' that might handle similar financial calculations.

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 of behavioral disclosure. It implies a write operation ('Add'), but does not specify permissions needed, whether the action is reversible, or any side effects (e.g., if adding duplicates is allowed). For a mutation tool with zero annotation coverage, this lack of detail is a significant gap.

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

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

The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core action without unnecessary elaboration, earning full marks for brevity and structure.

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

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

Given the tool's complexity (a write operation with 1 parameter), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It omits critical details like parameter meaning, behavioral traits, and usage context, making it inadequate for safe and effective tool invocation by an AI agent.

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

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

The input schema has 1 parameter with 0% description coverage, and the description does not mention the 'name' parameter at all. It fails to explain what the parameter represents (e.g., worksheet name), any constraints (e.g., length, uniqueness), or default behavior. With low schema coverage, the description does not compensate, leaving the parameter undocumented.

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 action ('Add') and resource ('new worksheet to the current workbook'), making the purpose specific and understandable. However, it does not distinguish this tool from sibling tools like 'excel_create_workbook' or 'excel_delete_worksheet', which limits differentiation in a server with many Excel-related tools.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as 'excel_create_workbook' for creating a new workbook or 'excel_write_worksheet' for modifying existing worksheets. There is no mention of prerequisites, like requiring an open workbook, or exclusions, which leaves usage context unclear.

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 of behavioral disclosure. While it explains the tool's purpose, it lacks critical behavioral details: it doesn't specify the output format (e.g., list of cell addresses, report), whether it modifies the worksheet (likely read-only but unstated), error handling, or performance considerations (e.g., time for large worksheets). For a tool with no annotation coverage, this is a significant gap.

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

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

The description is a single, clear sentence that efficiently conveys the core functionality without unnecessary words. It is front-loaded with the main action and goal, making it easy to understand at a glance. Every word serves a purpose, with no redundancy or fluff.

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

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

Given the tool's complexity (auditing cells for formula mismatches), lack of annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., a report, error list, or modified worksheet), how results are presented, or any behavioral constraints. For a tool with three parameters and no structured output information, more context is needed to guide effective 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?

The description mentions 'worksheet' and 'suspicious patterns' implicitly, but adds minimal semantic value beyond the input schema. With 67% schema description coverage (two parameters have descriptions, one does not), the baseline is 3. The description doesn't elaborate on parameter usage, such as how patterns are matched or what 'check numeric cells' entails in practice.

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 specific action ('audit a worksheet') and the precise goal ('find cells that should contain formulas but have hardcoded values'). It distinguishes itself from sibling tools like 'excel_validate_formulas' or 'excel_get_formulas' by focusing on detecting mismatches between expected formulas and actual hardcoded values, rather than validating existing formulas or retrieving them.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether the workbook must be open), compare it to similar tools like 'excel_validate_formulas' for formula checking, or specify scenarios where this audit is particularly valuable (e.g., compliance reviews or error detection).

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 states the action but fails to mention potential side effects (e.g., layout changes, data visibility impacts), permissions required, or error conditions. This leaves significant gaps for a mutation tool affecting workbook structure.

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, direct sentence with zero wasted words, clearly front-loading the core action and scope. It efficiently communicates the essential purpose without unnecessary elaboration, making it highly concise and well-structured.

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

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

For a mutation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits, error handling, or result format, leaving the agent with incomplete context to invoke the tool safely and effectively in complex scenarios.

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

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

The input schema has 100% description coverage, detailing all three parameters with defaults and meanings. The description adds no parameter-specific information beyond implying column width adjustment, so it meets the baseline for high schema coverage without compensating further.

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 action ('Auto-fit column widths') and scope ('for all worksheets in the workbook'), making the tool's purpose immediately understandable. However, it doesn't explicitly differentiate from the sibling tool 'excel_autofit_columns', which likely has a narrower scope, so it misses the highest score.

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, such as the sibling 'excel_autofit_columns' or other formatting tools. It lacks context about prerequisites, dependencies, or typical scenarios for application, offering minimal usage direction.

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 but only states the core behavior. It misses critical details: whether this modifies the workbook permanently, requires specific permissions, has side effects (e.g., overriding manual adjustments), or handles errors. For a mutation tool with zero annotation coverage, this is insufficient.

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

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

The description is a single, efficient sentence that front-loads the core purpose ('Auto-fit column widths') and includes key constraints. Every word earns its place with no redundancy or fluff, making it highly concise and well-structured.

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

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

Given the tool's moderate complexity (4 parameters, mutation operation) and lack of annotations/output schema, the description is adequate but incomplete. It covers the what but omits behavioral context, error handling, and usage guidelines, leaving gaps for an AI agent to infer safely.

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

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

Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds minimal value by mentioning 'min/max constraints' and 'padding multiplier', which align with schema details but don't provide additional syntax or usage insights beyond what's already structured.

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 action ('Auto-fit column widths') and resource ('based on content'), specifying the operation's scope. It distinguishes from 'excel_autofit_all_columns' by implying per-worksheet targeting, though not explicitly contrasting with that sibling tool.

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

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

No guidance is provided on when to use this tool versus alternatives like 'excel_autofit_all_columns' or other formatting tools. The description lacks context about prerequisites, target scenarios, or exclusions, offering only a functional statement.

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 of behavioral disclosure. It mentions a prerequisite ('requires data to be pre-loaded') but lacks details on permissions, output format (e.g., file type, location), error handling, or whether it modifies existing files. For a tool that creates files, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that front-loads the core action ('Create a native Excel chart') and includes a key constraint ('requires data to be pre-loaded'). There is no wasted wording, making it appropriately sized and well-structured.

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

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

Given the complexity of creating a chart with 4 parameters, no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose and a prerequisite but lacks details on behavioral aspects, output handling, or error cases, leaving gaps in completeness for a tool that generates files.

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

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

The input schema has 100% description coverage, so the schema already documents all parameters (outputFileName, chartType, dataMatrix, chartTitle). The description adds no additional meaning beyond the schema, such as examples or constraints, but the high schema coverage justifies the baseline score of 3.

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

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

The description clearly states the action ('Create a native Excel chart') and the resource ('from existing Excel data'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'excel_create_native_chart' or 'excel_create_business_chart', which might have overlapping functionality, so it misses full sibling distinction.

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 when to use it by stating 'requires data to be pre-loaded', suggesting it's for data already in Excel format. However, it provides no explicit guidance on when not to use it or alternatives among the many sibling tools, leaving usage context partially implied rather than fully clear.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Close' implies a mutation operation that might discard unsaved changes, but the description doesn't warn about data loss, permissions needed, or what 'current' refers to contextually. It lacks critical behavioral details for a mutation 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, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable without any structural 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?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'close' entails behaviorally (e.g., effects on unsaved data, error conditions, or post-close state), leaving significant gaps in understanding for safe agent 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?

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline high score for not adding unnecessary information.

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 'Close the current workbook' clearly states the action (close) and resource (current workbook), providing specific verb+resource. However, it doesn't distinguish from sibling tools like 'excel_save_file' or 'excel_delete_worksheet' which might also involve workbook state changes, so it misses full sibling differentiation.

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 (e.g., 'excel_save_file' before closing, or other workbook management tools). It lacks context about prerequisites, timing, or exclusions, leaving usage entirely implicit.

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 of behavioral disclosure. It states 'Apply conditional formatting,' implying a write/mutation operation, but doesn't clarify permissions, side effects (e.g., overwriting existing formatting), or error handling. This is inadequate for a tool that modifies data without safety annotations.

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

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

The description is a single, efficient sentence with no wasted words. It's front-loaded and to the point, though it could be more informative. The brevity is appropriate but borders on under-specification given the tool's complexity.

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 (3 parameters, nested rules object, no annotations, no output schema), the description is incomplete. It doesn't explain the input structure, expected behavior, or output, leaving significant gaps for the agent to infer usage. This is inadequate for a mutation tool with undocumented parameters.

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

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

Schema description coverage is 0%, so the schema provides no parameter details. The description mentions 'range' but doesn't explain the three required parameters (worksheetName, range, rules) or their semantics (e.g., format of range, structure of rules). It adds minimal value beyond the schema, failing to compensate for the coverage gap.

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 'Apply conditional formatting to a range' clearly states the action (apply) and target (conditional formatting to a range), but it's vague about the scope and lacks differentiation from sibling tools. It doesn't specify what 'conditional formatting' entails (e.g., rules, styles) or how it relates to Excel operations, making it less specific than ideal.

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. The description doesn't mention prerequisites, such as needing an open workbook or specific worksheet, nor does it differentiate from other Excel tools like excel_data_validation or excel_write_worksheet. This leaves the agent without context for tool selection.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool creates charts with 'intelligent defaults,' but does not clarify if this is a read-only or write operation, what permissions are needed, how errors are handled, or the output format. For a tool with no annotations, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that is front-loaded with the core purpose. It avoids redundancy and wastes no words, making it highly concise and well-structured for quick understanding.

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

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

Given the tool's complexity (4 parameters, nested objects, no output schema, and no annotations), the description is insufficient. It lacks details on behavioral traits, output format, error handling, and how it differs from sibling tools. The high schema coverage helps, but the description does not compensate for the missing contextual information needed for effective tool 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 description coverage is 75%, providing good documentation for most parameters. The description adds minimal value beyond the schema, mentioning 'business scenarios' and 'intelligent defaults,' which loosely relate to the 'businessScenario' parameter and implied defaults, but does not elaborate on parameter meanings or usage. With high schema coverage, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Create charts optimized for specific business scenarios with intelligent defaults.' It specifies the verb ('Create'), resource ('charts'), and key differentiator ('optimized for specific business scenarios'), but does not explicitly distinguish it from sibling tools like 'excel_create_financial_chart' or 'excel_create_dashboard_chart' beyond the 'business scenarios' focus.

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. It mentions 'business scenarios' but does not specify prerequisites, exclusions, or compare it to sibling tools such as 'excel_create_financial_chart' or 'excel_create_smart_chart', leaving the agent to infer usage context.

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

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

No annotations are provided, so the description carries the full burden. It states the tool creates a worksheet, implying a write operation, but lacks details on permissions, file handling, or output format. This is inadequate for a mutation tool with zero annotation coverage, as critical behavioral traits are missing.

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

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

The description is a single, efficient sentence that front-loads the key action and details. There is no wasted language, making it highly concise and well-structured for quick understanding.

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

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

Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks information on behavioral aspects, parameter meanings, and output details, which are essential for a tool that creates financial projections, making it insufficient for effective 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 description coverage is 0%, so the schema provides no parameter details. The description does not explain the parameters 'entityName' or 'worksheetName', nor their roles in the creation process. However, with only 2 parameters, the baseline is 4, but the lack of any parameter explanation in the description reduces it to 3, as it fails to compensate for the schema gap.

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 action ('Create') and the resource ('12-month cash flow projection worksheet'), specifying the content includes operating, investing, and financing activities. It distinguishes from generic creation tools but does not explicitly differentiate from sibling tools like 'cash_flow_forecast' or 'create_cash_flow_template', which have similar purposes, leaving some ambiguity.

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. The description does not mention prerequisites, context, or comparisons to sibling tools such as 'cash_flow_forecast' or 'create_cash_flow_template', leaving the agent without direction on selection.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'create' implies a write operation, the description doesn't specify whether this creates a new file or modifies an existing one, what permissions are required, whether it overwrites existing content, or what happens on failure. It mentions 'comprehensive data visualization' but doesn't explain what that entails behaviorally.

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

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

The description is a single, efficient sentence that gets straight to the point. It uses minimal words to convey the core functionality without any fluff or unnecessary elaboration. Every word serves a purpose in defining what the tool does.

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 3 parameters (including a complex nested object), 67% schema coverage, no annotations, and no output schema, the description is insufficient. It doesn't address the tool's behavior, error conditions, output format, or how it differs from similar chart creation tools in the extensive sibling list. The description leaves too many questions unanswered for proper 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?

The description mentions 'multi-series dashboard chart' which aligns with the primaryChart parameter containing series data, but adds no specific parameter semantics beyond what the 67% schema coverage provides. The schema already documents fileName, dashboardTitle, and primaryChart structure with types, categories, and series. The description doesn't explain parameter relationships or provide usage examples.

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 'create' and the resource 'multi-series dashboard chart' with the purpose of 'comprehensive data visualization'. It distinguishes from simpler chart tools like 'excel_create_native_chart' by specifying 'dashboard' and 'multi-series', but doesn't explicitly differentiate from similar siblings like 'excel_create_business_chart' or 'excel_create_financial_chart'.

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. With many sibling tools including various chart creation tools (excel_create_business_chart, excel_create_financial_chart, excel_create_smart_chart), there's no indication of what makes this dashboard chart tool different or when it's preferred over other visualization options.

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 of behavioral disclosure. It mentions 'pre-configured templates' but doesn't specify whether this tool creates new files, modifies existing ones, requires specific permissions, or handles errors. For a tool that likely involves file creation or modification, this is a significant gap in transparency about its behavior and potential side effects.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It avoids redundancy and wastes no words, making it easy to parse quickly. This is an example of optimal conciseness for a tool description.

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 (4 parameters, nested objects) and lack of annotations or output schema, the description is incomplete. It doesn't explain what the tool returns, how errors are handled, or the scope of its operations (e.g., file creation vs. modification). For a tool with this level of complexity, more contextual information is needed to ensure proper 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?

The description adds minimal meaning beyond the input schema. It mentions 'pre-configured templates', which aligns with the 'chartTemplate' parameter's enum values, but doesn't explain the semantics of 'data' or other parameters. With 75% schema description coverage, the schema does most of the work, so the baseline score of 3 is appropriate, as the description doesn't significantly compensate for the remaining 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's purpose: 'Create financial charts with pre-configured templates for common financial visualizations'. It specifies the verb ('Create'), resource ('financial charts'), and key feature ('pre-configured templates'), which is clear and informative. However, it doesn't explicitly differentiate from sibling tools like 'excel_create_business_chart' or 'excel_create_dashboard_chart', which likely have overlapping functionality, so it doesn't reach the highest score.

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. It doesn't mention any prerequisites, exclusions, or comparisons with sibling tools such as 'excel_create_business_chart' or 'excel_create_native_chart', leaving the agent to infer usage context. This lack of explicit guidance reduces its effectiveness in tool selection.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'create' which implies a write/mutation operation, but fails to detail permissions, side effects (e.g., file creation/modification), or output behavior (e.g., what the worksheet contains). This leaves significant gaps in understanding the tool's 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, efficient sentence with no wasted words, clearly front-loading the core action and purpose. It is appropriately sized for the tool's complexity, making it easy to parse quickly.

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 annotations, 0% schema description coverage, and no output schema, the description is incomplete. It does not address behavioral traits, parameter meanings, or output details, leaving the agent with insufficient context for a mutation tool that creates financial analyses.

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 for undocumented parameters. It does not mention any parameters (companyName, worksheetName) or their roles, failing to add meaning beyond the bare schema. This results in inadequate parameter guidance 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 action ('Create a financial ratios analysis worksheet') and the resource ('with GAAP-compliant ratio calculations'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'calculate_financial_ratios' or 'financial_ratios_analysis', which might offer similar functionality, so it falls short of a perfect score.

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, such as 'calculate_financial_ratios' or 'financial_ratios_analysis' from the sibling list. It lacks context on prerequisites, scenarios, or exclusions, leaving the agent with minimal usage direction.

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 creating a reference sheet but does not disclose behavioral traits such as whether this modifies an existing workbook, creates a new one, requires specific permissions, or has any side effects. For a tool with zero annotation coverage, this is insufficient 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 a single, clear sentence that efficiently conveys the core action. It is front-loaded with the main verb 'Create' and avoids unnecessary details, making it appropriately concise for the tool's apparent complexity.

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, no output schema, and a single undocumented parameter, the description is incomplete. It does not explain what the tool returns, how the reference sheet is structured, or any behavioral constraints. For a tool that likely generates content in Excel, more context is needed for effective 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?

With only one parameter and 0% schema description coverage, the description does not mention the 'worksheetName' parameter at all. However, since there is only one optional parameter, the baseline is high. The description could add value by explaining the parameter's role, but its absence is less critical given the low parameter count.

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

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

The description states the tool creates a 'comprehensive formula reference sheet with accounting standards and links', which provides a general purpose (create reference sheet) but lacks specificity about what 'comprehensive' entails or how it differs from sibling tools like 'excel_add_formula_with_documentation'. It's not tautological but remains somewhat vague about the exact output.

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. The description does not mention any context, prerequisites, or exclusions, nor does it differentiate from similar tools such as 'excel_add_formula_with_documentation' or other Excel-related siblings. This leaves the agent without usage direction.

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 of behavioral disclosure. It states the tool creates something, implying a write operation, but doesn't specify permissions needed, whether it modifies existing files, output format, or error handling. For a creation tool with zero annotation coverage, this is insufficient.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and includes key outputs, making it easy to parse quickly.

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 (a creation tool with 4 parameters), no annotations, and no output schema, the description is minimally adequate. It states what the tool does but lacks details on behavior, output, or usage context. It meets the bare minimum for a creation tool but doesn't provide comprehensive guidance.

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 doesn't mention any parameters explicitly. With schema description coverage at 75%, the schema documents most parameters well (loanAmount, annualRate, years, worksheetName). The description adds no additional parameter context, but the schema coverage is adequate, so the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Create a loan amortization analysis worksheet with payment schedule and accounting entries.' It specifies the verb ('Create'), resource ('loan amortization analysis worksheet'), and key outputs. However, it doesn't explicitly differentiate from sibling tools like 'loan_amortization' or other Excel creation tools, which would be needed for a perfect score.

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. There's no mention of prerequisites, context, or comparison to similar tools like 'loan_amortization' or other Excel creation tools in the sibling list. This leaves the agent without clear usage direction.

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 of behavioral disclosure. It states 'Create' which implies a write/mutation operation, but doesn't disclose any behavioral traits: no information on permissions required, whether it overwrites existing named ranges, error handling, or what the output looks like (since no output schema exists). The description is minimal and lacks critical context for safe and effective use.

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

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

The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by directly conveying the tool's purpose without redundancy or fluff.

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

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

Given the complexity (a write operation with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It states what the tool does but omits essential context: parameter details, behavioral expectations, error conditions, and output format. For a mutation tool with undocumented parameters, this minimal description is inadequate for reliable agent 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?

The input schema has 3 parameters with 0% description coverage, and the tool description provides no information about any parameters. It doesn't explain what 'name', 'range', or 'worksheetName' represent, their formats (e.g., Excel range syntax like 'A1:B10'), or examples. With low schema coverage, the description fails to compensate, leaving parameters entirely undocumented.

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 action ('Create') and resource ('a named range in the workbook'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'excel_add_worksheet' or 'excel_create_workbook' by focusing on named ranges, though it doesn't explicitly differentiate from all siblings. The description avoids tautology by not just restating the tool name.

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. It doesn't mention prerequisites (e.g., needing an open workbook), compare to similar tools (like 'excel_create_formula_reference' for references), or specify scenarios where named ranges are beneficial (e.g., for simplifying formulas or dynamic ranges). Usage is implied only by the tool's name and purpose.

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