Personal Finance MCP

Server Quality Checklist

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Latest release: v2.0.0
Disambiguation3/5
Many tools cover similar financial concepts (e.g., calculate_emergency_fund and calculate_contingency_fund, assess_risk_profile and suggest_asset_allocation), causing potential confusion. However, most tools have distinct descriptions that clarify their specific use case.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., calculate_future_value, plan_retirement). Verbs are descriptive and the pattern is maintained across all 77 tools.
Tool Count3/5
77 tools is high for a single MCP server, covering a vast range of personal finance calculators and metrics. While thorough, the count borders on overwhelming, and some tools are redundant (e.g., duplicate emergency fund tools).
Completeness4/5
The tool set covers an extensive range of personal finance domains: time value of money, loans, insurance, retirement, education, mutual funds, stocks, derivatives, and financial health. Minor gaps exist (e.g., tax planning), but the surface is remarkably comprehensive.
Average 3.6/5 across 77 of 77 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 23 commits in the last 12 weeks
- Last stable release on June 13, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as compounding assumptions, output format, or whether the calculation is annual or periodic. It only states the purpose without behavioral depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at two sentences, but this brevity comes at the cost of omitting necessary details. It is front-loaded with the core purpose, but every sentence earns its place only marginally.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (three numeric inputs) and presence of an output schema (unseen), some information might be elsewhere, but the description still lacks crucial context: no parameter definitions, no usage guidance, and no behavioral details. The agent is left with insufficient information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, meaning the parameters 'years', 'current_amount', and 'inflation_rate' have no explanations in the schema. The tool description does not define or clarify these parameters, leaving the agent to infer their meaning and units (e.g., inflation rate as a decimal or percentage).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the future cost after inflation, using 'Calculate future cost' and 'how much more you'll need.' It distinguishes the inflation adjustment aspect from generic future value calculations, though it doesn't explicitly differentiate from similar tools like 'calculate_future_value'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like 'calculate_future_value' or 'calculate_present_value'. The description does not provide any when-to-use or when-not-to-use instructions, which is a significant gap given the large number of sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description should disclose behavioral traits. It only mentions the calculations and that it includes 'assessments and benchmarks', but does not explain side effects, permissions, rate limits, or output format. The tool is likely read-only, but this is not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loads the key ratios. However, it could be slightly improved by structuring the list for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (7 parameters, no schema descriptions, no annotations), the description is incomplete. It does not explain the output schema (though one exists) or provide enough context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description provides no information about the 7 required parameters. It does not map parameters to ratios or explain expected input ranges/units, leaving the agent to infer from titles alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'calculate' and the resource 'key financial health ratios', listing specific ratios (Savings, Debt-to-Income, etc.). It clearly distinguishes from single-ratio tools like calculate_debt_to_income, though it may overlap with financial_health_check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., financial_health_check), prerequisites, or when not to use it. The description lacks any usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose any behavioral aspects such as being read-only, requiring authentication, or side effects. With no annotations provided, the description carries the full burden for transparency but fails to address this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but poorly structured. The example for expenses_json is embedded in the description, which could be better presented in a dedicated parameter description section. The first sentence is appropriate, but the rest is somewhat informal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is incomplete. It leaves two out of four parameters unexplained, lacks usage guidelines, and does not mention the output format despite an output schema existing. Given the schema coverage is 0%, more detail is expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an example for expenses_json and implies the use of monthly_income, adding some meaning beyond the schema which has 0% description coverage. However, the optional parameters existing_emis and existing_sips are not explained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes a household budget using the 50/30/20 rule, providing a specific verb and resource. It is distinct from many sibling financial calculators, though it doesn't explicitly differentiate from similar analysis tools like analyze_cash_flow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There are no prerequisites, when-not-to-use instructions, or comparisons with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose side effects, prerequisites, or safety (read-only nature). The brief description assumes analysis is safe but offers no explicit statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. Front-loaded with key purpose. Could add more detail without losing conciseness, but currently efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists, description need not detail return values. However, for a 6-parameter analysis tool, the description lacks completeness on scope and constraints. Adequate but minimal.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description mentions return and risk but does not map to specific parameters or explain units/format. Relies on parameter names being self-explanatory, which is insufficient for an AI agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it analyzes a two-asset portfolio for return, risk, and minimum variance weights, and finds the optimal allocation. This distinguishes it from sibling tools like calculate_portfolio_return which focus on single metrics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 (e.g., suggest_asset_allocation for multi-asset). The description implies use for two-asset portfolios but does not state limitations or provide context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must fully disclose behavior. It states outputs (variance, std dev, diversification) but doesn't mention input validation, return format, or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise (3 lines) with no wasted words, but lacks critical detail. Could be expanded without losing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Incomplete given complexity: missing input format requirements and no differentiation from many sibling tools. Output schema exists but description doesn't leverage it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only correlations parameter is described with an example. weights_json and std_devs_json are not explained at all, despite 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it calculates portfolio risk (variance and standard deviation) and shows diversification benefit, which is specific and distinguishes it from sibling tools like calculate_portfolio_return.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. The mention of 'diversification benefit' implies usage context, but there are no comparisons to alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions Newton-Raphson iteration but does not explain convergence issues, failure modes, input constraints, or output behavior. Without annotations, description should disclose more behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences that front-load the purpose, with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description lacks parameter explanations, edge case handling, and output details, making it incomplete for effective agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameter descriptions are given; schema coverage is 0%. Description does not clarify units (e.g., decimal vs percentage), default coupon frequency, or valid ranges.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Calculate Yield to Maturity' with the bond context and specifies the Newton-Raphson method, distinguishing it from sibling tools like bond price or duration calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, no prerequisites, and no conditions for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must disclose behavior. It mentions inflation adjustment and monthly SIP calculation, but omits details like required permissions, side effects, or output format. As a calculation tool, read-only nature is implied but not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with two sentences covering purpose and key features. It is front-loaded. However, it lacks structured formatting like bullet points that would improve readability for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters and an output schema, the description is minimal. It does not describe the output (e.g., SIP amount, future cost) despite the presence of an output schema. Parameter details are incomplete, and usage context is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description carries full burden. It adds context for inflation_rate (typically higher than CPI) and mentions SIP, but does not explain other parameters like current_savings, expected_return, child_current_age, education_start_age, or current_education_cost.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it plans for child's education expense, adjusting for inflation and calculating monthly SIP. This distinguishes it from siblings like 'plan_retirement' which focus on retirement. However, it could be more specific about the exact output or scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. While it implies use for child education planning, it does not mention siblings like 'plan_financial_goal' or 'calculate_sip_needed', nor does it state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the core calculation and purpose. However, with no annotations, it does not cover edge cases (e.g., tracking_error of zero), error handling, or any behavioral constraints beyond the basic formula.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The formula and purpose are front-loaded, making it easy for an agent to quickly understand the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mathematical tool, the description is minimal. It lacks parameter details, usage context, and behavioral transparency. Output schema exists but is not shown; however, the description does not leverage that to reduce burden. Given the sibling tool family, more completeness is expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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. While parameter names (portfolio_return, benchmark_return, tracking_error) are somewhat self-explanatory, the description does not define them or specify expected units/format, which is insufficient given no schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates Information Ratio using the formula Active Return / Tracking Error and measures consistency of outperformance vs benchmark. It is specific but does not differentiate from sibling ratio tools like Sharpe or Treynor, which could confuse an agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., Sharpe ratio, Treynor ratio). The description 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full burden for behavioral transparency. It mentions 'evaluates' but does not disclose whether this is a read-only calculation, any prerequisites, or consequence of inputs. Minimal safety context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, clear and front-loaded with the output. Efficient but lacks structure to group parameters or add usage hints.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema is present, so return details are covered elsewhere. Description covers main purpose and evaluation areas. Missing parameter-level detail makes it feel incomplete for a 10-input tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description lists categories (savings ratio, debt levels, etc.) which provides some context. However, it does not explain each of the 10 parameters individually (e.g., what 'Monthly Emis' means, format). Insufficient for a tool with 10 required params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes a 'financial health score (0-100) with rating and recommendations' and lists the evaluation factors. However, it does not differentiate from siblings like analyze_financial_ratios or assess_risk_profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for overall financial health assessment but gives no explicit guidance on when to use this tool versus alternatives like analyze_financial_ratios. No when-not or alternative tools mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It explains the core comparison logic (post-tax return vs effective loan cost) but does not mention assumptions like constant rates, time horizon, or whether the analysis is one-time or multi-year. More detail would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, no unnecessary words, and conveys the core idea efficiently. It could be slightly more structured with bullet points, but it is concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the decision and the presence of an output schema, the description covers the high-level purpose but omits details like assumptions, use cases, or limitations. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions for parameters (0% coverage), so the description should add meaning. It hints at 'post-tax' and 'effective loan cost', linking to the tax parameters, but does not explicitly describe each parameter or how they influence the calculation. The addition is minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares investing surplus vs prepaying a loan, using post-tax returns and effective loan cost. It distinguishes itself from siblings like compare_loans or calculate_prepayment_savings by focusing on the investment vs prepayment decision, though it could be more explicit about the output.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to prefer this tool over alternatives, such as compare_loans or calculate_prepayment_savings. The description implies usage when deciding between investing and prepaying, but lacks explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as computational assumptions (e.g., semiannual compounding), prerequisites, or side effects. The existence of an output schema reduces the need to describe return format, but other behavioral aspects 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the action and providing key interpretive context. Every sentence adds value, and there is no redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the output schema existing, the description lacks explanation of the output (e.g., convexity value meaning) and does not discuss assumptions or formula derivation. For a moderately complex financial tool, this is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description does not explain any parameters (e.g., units, expected ranges, input format). The agent receives no semantic help beyond parameter names and types, which is insufficient for a financial calculation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates bond convexity, a second-order interest rate risk measure, and provides an interpretation. This differentiates it from first-order measures like bond duration, among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly guide when to use convexity over alternative tools like calculate_bond_duration or calculate_ytm. The context implies convexity is for large yield changes, but this is not stated, 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not mention whether the operation is read-only, has side effects, requires authentication, or handles invalid inputs. The verb 'calculate' implies no state change, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences, no wasted words, and immediately states the purpose. It is well-structured for quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, 0% schema coverage, and no annotations, the description does not fully equip the agent. It fails to explain what the tool returns (output schema exists) or how parameters like monthly_emis affect results. The user must rely on the schema alone, which lacks descriptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description only partially covers parameters (monthly_expenses, dependents, job_stability). It omits monthly_emis and existing_emergency_fund, leaving their roles unclear. Default values exist in the schema, but the description adds minimal help.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: calculating emergency fund size (3-6 months of expenses). It specifies key adjustment factors (dependents, job stability), and the tool is distinct from siblings like calculate_contingency_fund, which may have a similar scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. Notably, sibling calculate_contingency_fund exists, and the description does not differentiate them, leaving the agent unaware of which to choose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The formula discloses the calculation method, which is useful for understanding behavior. However, with no annotations, there is no mention of edge cases, input validation, or any side effects, leaving gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: purpose followed by formula. No redundant information; every word serves a purpose. Very efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple financial calculation, the formula and parameter names provide adequate context. However, missing details on the compounding default and output schema limit completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the formula hints at the role of future_value, annual_rate, and years. The compounding parameter is not explained, and its default value is not mentioned, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate Present Value' and provides the formula, making the purpose obvious. However, it does not explicitly differentiate from sibling tools like calculate_future_value, relying on the name alone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as calculate_future_value or calculate_annuity_pv. The description only states what it does, not when to apply it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but only gives the formula and definition. It does not disclose behavioral traits such as assumptions (e.g., same period for returns), handling of negative beta, or required data consistency (e.g., annualized vs. periodic rates).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences. The formula is front-loaded, and every word is necessary. No redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and presence of an output schema, the description is minimally adequate. However, it lacks usage context and parameter details that are not covered by the schema or annotations, making it incomplete for an agent to confidently invoke.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description should clarify parameters. It mentions the formula but does not explain units (e.g., decimal vs. percentage) or input constraints. Parameter names are self-explanatory, but additional context would improve usability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the Treynor Ratio with the formula and explains what it measures (excess return per unit of systematic risk). It is specific and unambiguous, though it does not explicitly contrast with siblings like Sharpe or Sortino ratios.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as Sharpe ratio or Sortino ratio. The description lacks context on the appropriate scenario for Treynor ratio (e.g., well-diversified portfolios).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the formula and basic nature of zero-coupon bonds but does not disclose assumptions, rounding, output format, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loaded with the purpose. No unnecessary words, though it could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculation tool, the description is mostly adequate, but it lacks details on output (though output schema exists) and does not cover potential errors or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only implies parameter usage through the formula (FV, r, n). It does not clarify whether ytm is decimal or percentage, units, or constraints on values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool prices a zero-coupon bond and provides the formula. It distinguishes from sibling bond tools by being specific to zero-coupon bonds.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives like calculate_bond_price or other bond calculators. The description does not provide selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must convey behavioral traits. It implies the tool is a read-only analysis (no mutations), but does not explicitly state that it does not modify any data or require authentication. The presence of an output schema partially compensates, but more transparency about side effects or assumptions would improve this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences, no redundancy, and effectively front-loads the primary action. Every word adds value. It achieves clarity without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters and 0% parameter descriptions in the schema, the description does not sufficiently detail how to fill parameters (e.g., formats, ranges, examples). The output schema exists, but the description leaves the agent to infer parameter semantics from names, which may lead to incorrect invocations. A more complete description would include typical values or constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description hints at the purpose of parameters (investment amount, annual return, expense ratio, years) and the optional comparison, but it does not specify units (e.g., percentage for rates, currency for amount) or provide examples. With 0% schema description coverage, the description should offer more detail to guide correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool shows how expense ratio affects mutual fund returns over time, with an optional comparison feature. It uses a specific verb ('Show') and identifies the resource (expense ratio impact). While it distinguishes from sibling tools by focusing on expense ratio, it could be more precise about the mathematical nature (e.g., compounding).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like calculate_future_value or compare_lumpsum_vs_sip. It does not specify any prerequisites, when not to use it, or which specific scenarios benefit from the comparison feature. The description only mentions the optional comparison but lacks context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It mentions what is calculated but not assumptions (e.g., periodic compounding, standard bond structure). Does not disclose that it returns both duration values.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences with no redundancy. Clear and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, return values are covered. However, lacks context on bond type (standard coupon bond) and no mention of zero-coupon bond handling (separate tool exists). Adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet description adds no parameter explanations beyond what is obvious. Parameters like face_value, coupon_rate, ytm, coupon_frequency are not described.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it calculates Macaulay Duration and Modified Duration, which is a specific verb+resource. It differentiates from sibling bond tools like calculate_bond_price, calculate_ytm, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: use when duration is needed. But no explicit guidance on when to use vs alternatives (e.g., convexity for higher-order sensitivity), nor prerequisites like bond type assumptions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. The description only states that the tool calculates a ratio and suggests prudent EMI, but it does not disclose any behavioral traits, such as side effects, response format, or limitations (e.g., not considering living expenses). This is insufficient for a tool with zero annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (two sentences) and to the point. It front-loads the core purpose and then adds use cases. There is no unnecessary information, making it efficient. However, it could be slightly more structured by separating the use cases, but it is still concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple two-parameter calculator, and an output schema exists. The description provides the purpose and usage but lacks detail on parameter semantics. Given the simplicity, the description is minimally adequate, but the lack of parameter explanation and behavioral transparency makes it incomplete compared to a fully documented tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning no parameter descriptions are provided in the schema. The description does not explain what 'monthly_income' (e.g., gross vs. net) or 'monthly_emi_total' (includes all existing EMIs?) means. While parameter names are somewhat self-explanatory, the agent could misinterpret them, and the description should have added clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the debt-to-income ratio and suggests prudent additional EMI. It lists specific use cases like 'can I afford another loan' and 'loan eligibility', which helps distinguish it from sibling tools like analyze_financial_ratios. However, it does not explicitly differentiate from similar ratio tools, so it gets a 4.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage scenarios: 'Use for 'can I afford another loan', 'am I over-leveraged', loan eligibility.' This gives clear context on when to apply the tool. However, it does not mention when not to use it or suggest alternatives like loan_amortization for full amortization schedules, which prevents a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. However, it only mentions what the tool calculates (maturity and effective yield) and allowed compounding values. It does not describe rounding, precision, whether it returns total amount or just interest, or any caveats like early withdrawal or tax implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short: one sentence and a list of compounding options. It is front-loaded with the purpose and contains no irrelevant information. It could be considered minimally concise, though it could include more detail without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters (3 required) with no schema descriptions, and an output schema exists, the description should explain parameter meaning and usage. It only covers compounding options, leaving principal, annual_rate, and years undocumented. This is insufficient for a financial calculation tool where units and constraints matter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description does not explain any parameter. It only lists compounding frequencies, which hints at the 'compounding' parameter, but fails to describe 'principal', 'annual_rate', and 'years' (e.g., units, format, or valid range). This leaves the agent with insufficient guidance despite the schema defining the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates FD maturity and effective yield, lists compounding options, and explicitly states the use case ('Use for bank/NBFC FD maturity'). This distinguishes it from sibling tools like calculate_ppf or calculate_epf, which handle different instruments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a usage context ('Use for bank/NBFC FD maturity'), which implies its scope but does not explicitly state when not to use it or suggest alternatives. Sibling tools exist for similar fixed-income calculations, but no guidance on avoiding inappropriate usage is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It mentions the Fisher equation but does not address edge cases (e.g., negative rates, division by zero), assumptions, or output behavior. The formula is a start but insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, front-loading the purpose. Every word is relevant, and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculation tool with two parameters and an output schema, the description covers the core formula. However, it lacks context about typical usage, assumptions, or limitations, leaving gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate. While the equation implies that nominal_rate and inflation_rate are used as inputs, it does not clarify units (decimal vs. percentage) or value ranges, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate real (inflation-adjusted) rate of return' using the Fisher equation, providing a specific verb and resource. It distinguishes this tool from siblings like calculate_effective_rate or calculate_inflation_impact by naming the exact calculation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It lacks context such as prerequisites, typical scenarios, or comparisons with similar tools, which is needed given the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must convey behavioral traits. It indicates a read-only calculation by saying 'calculates', but doesn't explicitly state it's non-destructive or require authentication. The mention of 'accounts for inflation and pension shortfall' adds some context but is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loaded with the tool's label. The bullet-like list is efficient, though not perfectly structured. No unnecessary words, but could be slightly more organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's complexity (9 parameters, many siblings) and existence of an output schema, the description only covers a subset of inputs and calculations. It omits key aspects like the role of returns rates and current savings, making it incomplete for a comprehensive calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description only mentions a few of the 9 parameters (e.g., corpus, SIP, inflation, pension shortfall). It fails to explain key parameters like pre_retirement_return, post_retirement_return, and current_retirement_savings, leaving the agent without necessary context for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it's a 'comprehensive retirement planning calculator' and lists specific calculations (corpus needed, monthly SIP, inflation impact, pension shortfall). This distinguishes it from sibling tools like calculate_sip_needed which is more generic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. With many sibling tools in similar domains, the absence of usage context limits the agent's ability to choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only states basic functionality and annuity types. It lacks disclosure of assumptions (e.g., compounding per period), error handling, or limitations. The description does not compensate for the missing annotation context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no extraneous information. The first sentence defines the tool, the second explains the two annuity types. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits details critical for correct usage: frequency impact, rate format, and parameter interdependencies. For a moderately complex financial tool among many siblings, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds minimal value beyond parameter names. It explains that payment is periodic and annual_rate is per annum, but fails to clarify default frequency ('monthly') or how years and frequency interact. The annuity_type parameter is partially explained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it calculates future value of regular periodic payments (annuity/SIP) and distinguishes between ordinary and annuity due. This differentiates it from sibling tools like calculate_annuity_pv (present value) and calculate_future_value (single sum).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly conveys usage for annuity future value calculations but does not provide explicit when-to-use or when-not-to-use guidance relative to sibling tools. No mention of alternatives or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral traits. It only states it calculates a value, implying a read-only operation, but does not disclose any limitations, input constraints, or side effects. More detail needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, clear and front-loaded with no extraneous words. Every sentence provides useful context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description lacks detail on parameter usage and nuances like annuity type. For a tool with 5 parameters and no schema descriptions, the description is too sparse to be fully actionable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning to parameters. It mentions 'regular periodic payments' which links to 'payment', 'years', and 'frequency', but does not explain 'annual_rate', 'annuity_type', or their defaults. The description adds minimal value beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates present value of regular periodic payments, using a specific verb and resource. It also provides practical use cases (loan payments, pension, lease payments), which differentiates it from sibling tools like calculate_present_value (single sum) and calculate_annuity_fv (future value).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions use cases but does not explicitly guide when to use this tool over siblings. There is no mention of when not to use it or alternatives, leaving the agent to infer based on tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It only mentions the formula, not edge cases (e.g., zero division with negative values), error handling, or whether it returns a decimal or percentage. The behavioral context is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with essential information, front-loaded with purpose. However, the second sentence repeats the formula which could be inferred from the name, making it slightly redundant. Still efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and low schema coverage, the description omits important context like return format, error conditions, and prerequisites. The existence of an output schema partially mitigates the lack of return documentation, but usage guidance is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 names start_value, end_value, and years in the formula but does not define their meaning, valid ranges, or examples. The description adds only partial value beyond the schema property titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates CAGR, provides the formula, and identifies it as a standard measure for investment returns. It effectively differentiates from sibling tools that handle other financial calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use CAGR vs other tools like calculate_future_value or compare_loans. The description implies it's for investment returns but lacks when-not-to-use or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it accounts for existing savings and expected returns, which adds some behavioral context. However, it does not disclose error handling, units of output (monthly amount), or assumptions like compounding frequency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences. The first states the core purpose, the second adds crucial context. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate. It covers the key inputs and purpose but omits details like return value format or whether rounding is applied.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage. The description adds meaning by linking 'existing savings' to current_savings and 'expected returns' to annual_rate. It does not explain target_amount or years beyond their names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate monthly savings required to reach a financial target,' specifying the verb and resource. It distinguishes from sibling tools like calculate_sip_needed by focusing on a generic monthly savings goal, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for financial goal planning but provides no explicit guidance on when to use this tool versus alternatives like calculate_sip_needed or calculate_future_value. No exclusions or when-not-to-use are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as whether the tool returns a recommendation, how it handles edge cases, or any side effects. The output schema exists, but the description itself lacks transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with one sentence and an example, front-loading the purpose. However, it could elaborate slightly on the analysis logic without being wordy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (though not shown), the description need not explain return values in detail. However, it lacks context on how the analysis is performed, which would help agents judge appropriateness. Adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 adds meaning for the debts_json parameter via an example, but does not explain consolidated_rate or consolidated_tenure_years beyond their names. This partial coverage justifies a 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: analyzing if consolidating multiple debts into one loan makes sense. It also provides a concrete input example, distinguishing it from sibling financial calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for debt consolidation analysis but does not explicitly state when to use this tool versus alternatives like compare_loans or calculate_emi. No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must carry burden. It discloses the formula and purpose, but does not mention any side effects, input format, or output structure. For a simple computation, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with the formula front-loaded. No wasted words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, output schema exists), the description is largely complete. It covers the formula and purpose, though adding input unit guidance would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet description only mentions nominal rate and compounding implicitly through the formula. It does not clarify input units (decimal vs percentage) or list compounding options beyond default 'monthly'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it calculates Effective Annual Rate from nominal rate and provides the formula. It implies a specific financial computation but could differentiate more explicitly from sibling tools like calculate_real_return.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for comparing rates with different compounding but does not explicitly state when to use this tool versus alternatives like calculate_future_value or calculate_real_return.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the use of the 100-age equity rule with adjustments and its role as the authoritative split calculator. Without annotations, it does not describe error handling, state changes, or limitations, but offers reasonable insight into its method.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise, with main purpose upfront, no redundant sentences. Could be slightly more structured but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Provides enough context for a suggestion tool, but lacks detail on output structure (e.g., whether percentages, amounts, or both). With an output schema present, the description could be leaner; however, given no annotations, it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% but description clarifies risk_profile values and the effect of monthly_investment. Other parameters (age, investment_horizon_years) receive no additional explanation, partially compensating for schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it suggests asset allocation based on age, risk profile, and horizon. Mentions the 100-age equity rule and relationship to sibling assess_risk_profile, but lacks explicit differentiation on when to choose one over the other.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides some guidance: it is the single source of truth for the split and mentions assess_risk_profile returns same numbers. Also notes that passing monthly_investment yields per-bucket amounts. However, no explicit when-not-to-use or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description bears full responsibility. It mentions the formula and constraint, but does not explain the output format, potential errors, or whether it's a read-only calculation. Lacks detail on dependencies and 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (three sentences), front-loaded with purpose, and includes the formula and a key constraint. No unnecessary words, though it could be slightly more descriptive without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the three required parameters, no schema descriptions, and no annotations, the description is incomplete. It does not explain the output (likely a stock value), units, or potential error conditions. The output schema exists but is not referenced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description does not individually explain the three parameters. It uses D1 in the formula without clarifying that D1 = current_dividend * (1+growth_rate). Growth_rate and required_return are not defined. Insufficient compensation for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it values a stock using the Gordon Growth Model (DDM), provides the formula, and specifies it's for stable dividend-paying companies. This distinguishes it from sibling tools like value_stock_two_stage_ddm and value_stock_dcf.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a condition ('For stable, dividend-paying companies') and a constraint ('required_return must be > growth_rate'), but does not explicitly state when not to use this tool or provide alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description alone must disclose behavioral traits. It explains the calculation logic (fair price formula, optional PEG ratio) but does not mention limitations (e.g., P/E inappropriate for negative earnings) or side effects. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. The first sentence states the purpose and formula; the second adds optional functionality. Could benefit from structured listing of parameters but remains efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite an output schema documenting return values, the description is incomplete for a tool with 4 parameters and 0% schema coverage. It explains the required parameters but omits descriptions for optional parameters (company_growth, industry_growth) and their role in PEG calculation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must clarify each parameter. It explains 'eps' and 'industry_pe' via the formula but does not define 'company_growth' or 'industry_growth' beyond implying they relate to PEG ratio. Optional parameters are left for the agent to infer.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool values a stock using P/E ratio relative valuation, provides the formula (Fair Price = EPS × Industry P/E), and mentions optional PEG ratio calculation. It distinguishes from sibling valuation tools like DDM or DCF by specifying the method.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for P/E-based relative valuation but provides no explicit guidance on when to use this tool versus alternatives (e.g., DDM for dividend stocks, DCF for cash flow analysis). No when-not-to-use conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It includes the formula and frequency mapping but lacks details on assumptions (e.g., clean vs dirty price, day count), error handling, or return format. The description is insufficient for a complete understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (3 sentences) and front-loaded with purpose. Each sentence adds unique value: statement of what the tool does, the formula, and clarification of coupon_frequency values. No extraneous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (financial calculation with 5 parameters) and that an output schema exists, the description is adequate but not thorough. It covers the core formula and frequency but omits assumptions, edge cases (e.g., zero-coupon bonds), and practical usage notes. Comparable to tools like calculate_present_value which similarly rely on schema for details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should clarify parameter meanings. It explains coupon_frequency values (1=annual, 2=semi-annual, 4=quarterly) which adds value, but other parameters like face_value, ytm are only covered by the formula notation (C, r, FV) without explicit mapping. The schema names are self-explanatory, but the description helps marginally.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Calculate bond price using DCF of coupon payments and face value.' It provides the formula and explains coupon_frequency values, distinguishing it from sibling tools like calculate_ytm or calculate_zero_coupon_bond.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for bond pricing but does not explicitly state when to use this tool versus alternatives like calculate_ytm or calculate_current_yield. There is no guidance on exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden. It discloses that contributions are monthly compounding and includes salary growth. However, it does not describe what the output contains or any assumptions about withdrawal rules or taxes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that are front-loaded with the core purpose, followed by a use-case hint. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's apparent simplicity and the presence of an output schema (not shown), the description is borderline adequate. It covers the main functionality but misses parameter guidance and does not leverage existing structured metadata.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the description does not elaborate on any of the 6 parameters. Parameter names like 'monthly_basic' are self-explanatory, but the description provides no additional meaning or usage hints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it calculates EPF retirement corpus with salary growth and monthly compounding. The tool name and description align, but it does not explicitly differentiate from sibling tools, many of which are other financial calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a specific use case: 'how big will my EPF/PF be at retirement'. This tells the agent when to select this tool. However, no when-not or alternative tool suggestions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 doubles money and returns the tenure, but it does not specify assumptions like compounding frequency, output unit (years vs. months), or handle edge cases. Minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, consisting of two sentences. However, the first sentence uses a dash and semicolon that slightly impair readability. Overall, it is efficient and each part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core purpose and a specific use case. An output schema exists, so return values are likely documented there. Still, for a simple tool with no annotations, the description could be more detailed, such as specifying that the tenure is in years.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description only implicitly mentions the interest rate ('at the given interest rate') and does not explain the principal parameter. With 0% schema description coverage, the description should compensate by clarifying both parameters, but it falls short.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: it returns the tenure required for doubling money in KVP at a given interest rate. The verb 'returns' and resource 'tenure for KVP' are specific, and the phrase 'how long to double my money in KVP' distinguishes it from other financial calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides an explicit use case ('Use for 'how long to double my money in KVP''), which gives context for when to use the tool. However, it does not mention exclusions or alternative tools (e.g., rule_of_72), which would help distinguish it from similar calculations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It mentions output (interest saved, tenure reduction) but does not clarify side effects, permissions, or limitations. For a calculator, read-only behavior is implied but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, two sentences with no fluff. Front-loaded with purpose and key outputs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 6 parameters and no schema descriptions, the description is insufficient. Does not explain how to specify prepayment options or interpret results. Lacks details on output schema despite its existence.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description only names generic terms like 'principal, annual rate, tenure years' without explaining each parameter's meaning or units. Does not map 'extra EMI or lump sum' to specific parameters like monthly_prepayment or lump_sum_prepayment.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool calculates savings from loan prepayment, showing interest saved and tenure reduction. It mentions extra EMI or lump sum, which distinguishes it from related siblings like compare_loans or loan_amortization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. Does not differentiate from alternatives like invest_or_prepay_loan. Purpose is clear, but lacks directional context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It gives the formula but does not disclose handling of edge cases (e.g., negative standard deviation) or expected input formats (decimal vs percentage). For a simple calculation, it is minimally transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, no redundant information, and immediately communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description adequately covers the core calculation. It could mention that output is a number, but the formula implies it. Nearly complete for a straightforward math tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not explain the three parameters beyond their presence in the formula. It lacks definitions of units, constraints, or typical ranges, failing to compensate for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the Sharpe ratio, provides the formula, and defines it as risk-adjusted return per unit of risk. It distinguishes itself from sibling tools like calculate_sortino_ratio or calculate_treynor_ratio by name and formula.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions, leaving the agent without decision support among many ratio calculators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must fully disclose behavior. It mentions outputs but does not disclose assumptions like compounding frequency, payment timing (beginning/end of period), or how step-up is applied. This is a significant gap for a financial calculation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler. Front-loaded with tool purpose, then lists outputs, then parameter detail. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return values are covered. However, missing assumptions about compounding and payment timing leave the model uncertain. Adequate but not thorough for a financial tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description explains the optional step_up_percentage parameter with an example. Other parameters are self-explanatory from names, but units (e.g., annual return as percentage) are not explicitly stated. Partially compensates for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates SIP returns and lists key outputs (future value, total invested, wealth gained). It distinguishes from sibling tools like calculate_sip_needed which computes required SIP amount.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for SIP return calculation but does not specify when to prefer this over related tools like compare_lumpsum_vs_sip. No explicit guidelines on prerequisites or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 the output is a schedule and notes the trend, but omits assumptions like monthly compounding, payment frequency, or output schema details. The output schema exists but the description does not leverage it for behavioral clarity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loaded with the main purpose. It could be more structured (e.g., bullet points) but is efficient and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of financial calculations, the description is adequate but incomplete. It lacks assumptions about payment frequency, compounding period, and edge cases. The output schema exists, which reduces the need for return-value explanation, but core behavioral assumptions are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must add meaning beyond parameter names. However, it does not explain units (e.g., annual_rate as decimal or percentage), valid ranges, or that tenure_years should be a positive integer. The description provides no additional parameter guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a loan amortization schedule showing month-wise principal/interest split, with the trend of decreasing interest and increasing principal. This is a specific verb+resource combination that distinguishes it from sibling tools like calculate_emi (which only gives EMI) and compare_loans.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for generating a full schedule, but lacks explicit guidance on when to use vs. alternatives or exclusions. For instance, it doesn't clarify that this tool is for a fixed-rate loan or that tenure must be in years.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose behavioral traits (e.g., read-only, side effects, required permissions). It only provides input examples, leaving the agent unaware of important safety or authorization details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (two sentences) and front-loaded with the core purpose. Every sentence provides essential information with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters and an output schema (not shown), the description is minimally viable. It provides the core purpose and example inputs but lacks details on output structure, error handling, or edge cases. The presence of an output schema reduces the need to describe returns, but completeness is still modest.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning to parameters by showing concrete example formats for target_allocation_json and current_values_json (e.g., '{"equity": 60, "debt": 30, "gold": 10}'). This compensates for the 0% schema description coverage, though it does not explain the optional additional_investment parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 trades needed to rebalance portfolio to target allocation.' It uses a specific verb and resource, and the example distinguishes it from sibling tools like suggest_asset_allocation, which gives allocations but does not calculate trades.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool vs. alternatives like suggest_asset_allocation or calculate_portfolio_return, nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only lists output metrics without disclosing behavioral aspects such as whether it requires external data, assumptions used, or limitations. For a tool with no annotations, more transparency is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Exceptionally concise: two sentences that pack purpose, outputs, and usage trigger without any wasted words. The structure is front-loaded with the core analysis description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers basic usage and outputs, which is adequate for a simple analysis tool. However, given the extensive sibling list (e.g., 'analyze_budget', 'financial_health_check'), more differentiation and context on how this tool fits among them would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not elaborate on parameters beyond their names. It does not explain how 'emi' differs from other expenses or provide ranges or formatting, leaving agents to infer from parameter names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it performs household cash-flow analysis computing monthly surplus, savings rate, and expense ratio. Also provides specific user query examples, making the tool's purpose unmistakable and distinguishing it from generic financial calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: when user describes income/spending and asks about financial health or savings potential. However, does not mention when not to use or provide alternatives among the many sibling tools like 'analyze_budget'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It does not disclose any behavioral traits beyond the formula, such as division-by-zero handling (e.g., if market_price is zero), accuracy, or output specifics. The output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that directly states the tool's purpose and formula. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculation tool, the description covers its core purpose. The presence of an output schema reduces the need to describe return values. However, lacking usage guidance and edge-case behavior leaves minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description maps parameters to financial terms: 'dividend_per_share' is explained as 'Annual Dividend' and 'market_price' as 'Market Price'. This adds meaningful context beyond the raw parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates dividend yield using the formula 'Annual Dividend / Market Price × 100'. It uses a specific verb ('Calculate') and resource ('dividend yield'), distinguishing it from sibling tools like calculate_current_yield or calculate_ytm.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as 'calculate_current_yield' or other yield calculations. The context or prerequisites for using dividend yield are not mentioned, 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only describes the calculation and input format, with no mention of side effects, permissions, validation, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and includes helpful examples. It could be slightly more structured, but it is efficient and front-loads the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists (not shown), so return values are covered. However, the description lacks details on edge cases, validation, or expected behavior for invalid inputs, making it adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explains that parameters expect JSON maps of name:value pairs and provides concrete examples, adding significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate net worth from assets and liabilities,' specifying the verb and resource. It distinguishes from sibling tools (e.g., calculate_future_value) which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, but the purpose is self-explanatory. Examples are provided for input format, but no exclusions or contextual cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 implies a read-only calculation but does not explicitly state that the tool has no side effects, requires no authentication, or any other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the main purpose, and includes relevant examples. It could be more structured but is efficient and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and schema descriptions, the description covers the essential use case but misses some parameter constraints (e.g., positive values). The existence of an output schema mitigates the need to explain return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description adds meaning by specifying allowed values for option_type ('call|put') and position ('long|short'). Other parameters (strike, premium, spot_at_expiry) are only implied in examples, not formally described.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates payoff, profit/loss, and breakeven for an option leg at expiry, with specific examples. It distinguishes itself from many sibling financial calculation tools by focusing on options.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear examples of when to use the tool (e.g., P&L calculation, breakeven, max profit/loss). However, it does not mention when not to use it or alternatives like calculate_black_scholes or calculate_put_call_parity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the tool's purpose but does not mention assumptions (e.g., constant returns, no fees) or side effects. Adequate for a simple calculation tool but could be more transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, no unnecessary words. It front-loads the acronym expansion and purpose. Could be slightly more structured but is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 required numeric inputs) and the presence of an output schema, the description adequately covers the core functionality. However, it misses potential edge cases or limitations, such as early depletion scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain parameter units (e.g., whether annual_return is a percentage or decimal) or clarify that corpus is initial amount. The names are partially self-explanatory, but the lack of detail reduces clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates how long an investment corpus lasts with regular withdrawals, using a specific verb and resource. It distinguishes itself from sibling tools like calculate_future_value and calculate_present_value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for SWP sustainability calculations but provides no explicit guidance on when to use or not use this tool versus alternatives among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only states what the tool compares but does not disclose behavioral aspects like output format, assumptions (e.g., SIP frequency), or that it is a pure calculation without 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, front-loading the purpose and defining key terms. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema (not shown but indicated), the description is adequate for basic understanding. However, it lacks details about the comparison output format or any assumptions about SIP frequency (e.g., monthly), which could improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not add meaningful detail beyond the parameter names. It states 'total_amount', 'annual_return', and 'years' but omits units, decimal/percentage format, or constraints (e.g., non-negative).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The tool name and description clearly state it compares lump sum vs SIP investment for the same total amount, with explicit definitions of each. This distinguishes it from sibling tools like calculate_sip_returns or calculate_future_value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (comparing two investment strategies) but does not explicitly exclude other cases or mention alternatives. The unique comparison logic makes it distinct enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries full responsibility for behavioral disclosure. It mentions the two-stage structure but does not explain assumptions (e.g., constant stable growth rate, requirement for dividend payment) or limitations (e.g., sensitivity to growth rate estimates). The description is adequate but not rich enough to fully inform an agent of behavioral traits beyond the basic model outline.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using just two sentences to convey the model's purpose and structure. It is front-loaded with the key identifier, and every word contributes to understanding. No irrelevant information is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a two-stage DDM tool, the description is minimal. It lacks details on assumptions, input constraints, or typical use cases. While an output schema exists (reducing need to explain returns), the description does not sufficiently equip an agent to use the tool correctly in varied scenarios, especially compared to simpler sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 'current dividend', 'high growth rate', 'high growth years', and 'stable growth rate', but does not elaborate on their meanings or units (e.g., annual vs. total growth). The 'required_return' parameter is not mentioned at all. The description adds only marginal semantic value over the parameter titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a 'Two-stage DDM' for companies transitioning from high growth to stable, and specifies the two stages (high growth dividends discounted, Gordon model terminal value). This efficiently distinguishes it from sibling tools like 'value_stock_ddm' (single-stage) and 'value_stock_dcf' (discounted cash flow), which are listed nearby.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for companies with initial high growth that later stabilize, but does not explicitly state when to use this tool versus alternatives like the single-stage DDM or DCF. No exclusions or comparisons are provided, leaving the agent to infer context from the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It includes that volatility is annualized in percent, but does not disclose assumptions like no dividends or early exercise, nor does it specify the output structure beyond delta and price.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences and an additional line for volatility. It is front-loaded and contains no unnecessary words, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the presence of an output schema, the description omits key assumptions (e.g., no dividends, European style) and does not elaborate on half of the parameters. This leaves agents without enough context to use the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description only explains the volatility parameter (annualized percent). Other parameters like spot, strike, years, annual_rate, and option_type lack any semantic explanation, requiring inference from titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates the theoretical European option price (Black-Scholes) and delta, with specific use cases like fair option premium and implied pricing. It distinguishes itself from siblings such as calculate_option_payoff and calculate_put_call_parity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases ('what is a fair option premium', option valuation, implied pricing) but does not mention when to avoid using this tool or differentiate from siblings like calculate_option_payoff.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It explains the formula but does not disclose potential traps like division by zero, input constraints, or output format (though output schema exists). Behavior is transparent for a simple calculator, but limited depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first gives the formula, second explains interpretation. No filler words; essential information is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is a simple calculation with output schema (not shown). Description covers the core purpose and interpretation but omits practical context like expected input ranges, edge cases, or how to interpret the result (e.g., positive alpha indicates skill). Adequate for a knowledgeable user, but leaves gaps for novices.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no parameter descriptions), but parameter names (portfolio_return, risk_free_rate, beta, market_return) are self-explanatory and the formula clarifies their roles. The description adds no further detail beyond the formula, so it minimally compensates for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates Jensen's Alpha via the formula and interprets it as 'excess return over CAPM expectation' and 'measures portfolio manager's skill'. It distinguishes itself from sibling financial performance tools by specifying a unique formula and interpretation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives like Sharpe, Treynor, or Sortino ratios. It implies usage for evaluating portfolio manager skill relative to CAPM, but lacks direct guidance on selection criteria or contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description implies a pure calculation with no side effects, but does not explicitly state read-only nature or any behavioral constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise—two essential lines with no redundant text, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Explains inputs and calculation, but lacks any usage context or description of output; presence of output schema partially compensates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description explains each parameter via the formula (total_assets, total_liabilities, units_outstanding), adding meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Calculate Mutual Fund NAV' with the formula, distinguishing it from retrieval tools like get_mutual_fund_nav and other financial calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use vs alternatives; no mention of prerequisites or exclusions despite numerous sibling calculation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It discloses annual compounding and default tenure, but does not mention assumptions like constant annual deposit, maximum deposit limits, or that the rate is assumed fixed (PPF rate changes periodically). Some behavioral traits are left implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the key verb and resource. It is efficient, though the second sentence could be slightly more structured (e.g., bullet points). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is an output schema (not shown), so return value details are not required. However, the description does not mention constraints like PPF's maximum annual deposit or rate variability, which are important for realistic use. It is adequate but not fully comprehensive for the typical PPF context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the description adds no parameter info beyond the schema. It only mentions the default for 'years' (15) and implicitly the rate (7.1%), but does not explain 'annual_deposit' or 'annual_rate' semantics. For a 3-parameter tool with no coverage, the description should compensate more.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates PPF maturity value for a fixed yearly deposit, and provides use cases like 'how much will my PPF grow to' and 'PPF maturity/corpus'. It effectively distinguishes from sibling tools by specifying the PPF investment type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use for ...' and gives concrete scenarios. However, it does not mention when not to use this tool or point to alternatives among many sibling tools, like compound interest calculators or other small savings schemes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose behavioral traits. It does not mention what the tool returns (output schema exists but not described), whether it is read-only, or any side effects. The lack of output description limits transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with two sentences and an example. Every sentence adds value: purpose, input format, and a concrete example. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists but is not described, the description omits what the tool returns (e.g., best deal, comparison table). It also does not cover edge cases. For a comparison tool, understanding output is important, so completeness is moderate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description compensates by explaining the expected JSON structure with fields (principal, annual_rate, tenure_years, name) and provides an example. However, it does not elaborate on constraints or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares multiple loan options to find the best deal, specifying input format and fields. It distinguishes from siblings like 'calculate_emi' and 'loan_amortization' which handle single loans or other analyses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for comparing multiple loans but lacks explicit guidance on when to use versus alternatives like 'calculate_emi' or 'invest_or_prepay_loan'. No 'when not to use' or alternative suggestions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 computes target and shortfall but does not disclose any side effects, permissions, or detailed behavior beyond that. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, no wasted words. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers the essential purpose and usage for moderate complexity. Could explain how the shortfall is derived (e.g., target - existing_fund) but output schema exists, so return values are not required. Good enough for a calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% parameter descriptions. The description mentions 'monthly_expenses' and 'months_target' implicitly via the recommendation but does not describe 'existing_fund'. It partially compensates but not fully for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool calculates contingency/emergency fund target and shortfall. However, there is a nearly identical sibling 'calculate_emergency_fund' and no distinction is made, so it's not fully differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit example questions ('how big should my emergency fund be', 'am I covered if I lose my job') and a recommendation (3-6 months of expenses, 12 if irregular). Does not mention when not to use or alternatives, but the guidance is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description clearly states the calculation formula, making the tool's behavior transparent. No annotations exist, but the tool is a pure mathematical function with no side effects; however, an explicit statement of 'no side effects' would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that conveys the essential formula with no unnecessary words, perfectly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description defines the core purpose but omits parameter details and usage context. Given the presence of an output schema and the tool's simplicity, it is minimally adequate but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter meaning is only implied by the formula; no description clarifies units (e.g., annual coupon as dollars or decimal, market price as dollars). With 0% schema description coverage, the tool description fails to compensate adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the formula 'Current Yield = Annual Coupon / Market Price × 100', clearly identifying the tool's purpose and distinguishing it from sibling tools like YTM or bond price calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for computing current yield but provides no guidance on when to use this tool versus alternatives (e.g., YTM for total return) or what inputs are appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It explains the calculation formula and purpose, which is helpful. However, it does not describe the output format or any prerequisites like required permissions, leaving some behavioral aspects undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: two sentences and a formula. Every part carries meaning, and it is front-loaded with the core purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 4 required parameters and no annotations. The description provides the calculation formula and usage context but omits parameter details and output description. Given the output schema exists, the description is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. The description only mentions variables in the formula (β, Value, Index, Lot Size) but does not explicitly explain them or their constraints. This provides minimal value beyond the schema's parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the number of index-futures contracts for hedging an equity portfolio. It includes the formula and uses specific terms like 'beta hedging' and 'downside protection', distinguishing it from siblings like calculate_futures_price or calculate_option_payoff.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly suggests use cases: 'how do I protect/hedge my portfolio against a market fall', beta hedging, downside protection. It provides clear context for when to use, though it doesn't mention when not to use or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description transparently discloses it is a calculation (no side effects), provides the formula, and describes compounding options, though it does not mention error handling or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancy: the first states the purpose, the second provides the formula and compounding options. Every word contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core purpose and formula, but given the 0% schema coverage and 4 parameters, it could be more complete by explaining parameter units or format (e.g., rate as decimal). The output schema exists but its content is not referenced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only elaborates on 'compounding' with examples, leaving present_value, annual_rate, and years meaningfully undescribed beyond what the schema names suggest.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates future value of a lump sum investment with compounding, includes the formula, and lists compounding frequencies, distinguishing it from related siblings like calculate_present_value and calculate_annuity_fv.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies it is for lump sum investments and lists compounding options, but does not explicitly state when to use vs alternatives or exclude scenarios like periodic payments.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description merely states it 'calculates' without explicitly noting that it is a read-only computation without side effects. However, the verb implies a safe operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that front-load the purpose and formula without unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description explains the core formula and parameters adequately. It lacks mention of edge cases or return value details, but is sufficient for a calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning by explaining the HLV formula, mapping most parameters (annual_income, years_of_income_to_replace, outstanding_loans, future_goals_corpus, existing_insurance) to components. The 'existing_investments' parameter is not explained, but overall the formula provides context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates life insurance need using the HLV method, with a specific verb and resource. It distinguishes from sibling calculation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 calculate_future_value or other insurance-related tools. The description does not specify prerequisites or typical scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that it handles lump-sum, interest reinvested, annual compounding, and typical 5-year tenure. However, it does not mention edge cases (e.g., zero years, negative principal) or output rounding, though the presence of an output schema mitigates some lack of detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's essence: 'NSC maturity' followed by key details. Every word adds value, and the structure is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity and the presence of an output schema, the description is adequate but could be more complete. It does not specify the return value format (e.g., maturity amount vs. interest breakdown), and it lacks references to the Indian context. However, it covers the main mechanics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not elaborate on parameters. While parameter names (principal, years, annual_rate) are clear, the description omits units (e.g., annual_rate as percentage vs decimal). This creates ambiguity, especially since the default is 7.7 (likely percentage).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes NSC maturity, with specifics on lump-sum, reinvested interest, annual compounding, and typical 5-year tenure. It distinguishes from siblings by explicitly naming 'NSC', a unique Indian savings scheme.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for NSC maturity calculation but provides no explicit guidance on when to use this tool versus alternatives like calculate_future_value or other small-savings scheme calculators. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not mention error handling, data validation, or assumptions (e.g., inputs must be JSON arrays, returns as percentages). The example helps but lacks thoroughness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: two sentences plus a formula and example. The main purpose is stated first, and the rest provides additional context without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, clear formula, output schema exists), the description is sufficient. It covers the core calculation and input format. Minor gaps: no mention of limitations or edge cases, but overall complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no descriptions), so the description must compensate. It explains weights and returns as JSON arrays with an example, adding meaning beyond the schema's string type. However, it could be more explicit about the format (e.g., 'provide as JSON string').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate expected portfolio return', a specific verb and resource. It includes a formula and example, distinguishing it from sibling tools like calculate_portfolio_risk.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides the formula and example but does not explicitly state when to use this tool versus alternatives like analyze_two_asset_portfolio or calculate_portfolio_risk. Usage context is implied but not differentiated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully convey behavioral traits. It discloses that the tool calculates quarterly interest income and principal at maturity. However, it does not mention any constraints, assumptions, or side effects (e.g., minimum principal, tax implications). The description is adequate but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, front-loading the purpose and usage. Every word adds value with no unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and existence of an output schema, the description does not need to detail returns. However, with three parameters and no schema descriptions, the description should provide more context about parameter meaning and defaults. It only partially covers the required parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It only mentions 'principal' implicitly through context ('quarterly interest income and the principal returned'). It does not explain the 'years' or 'annual_rate' parameters, nor that default values are provided. This is insufficient for guiding proper parameter filling.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as calculating SCSS (Senior Citizens Savings Scheme) quarterly interest and principal at maturity. It distinguishes itself from other financial calculators by focusing on this specific government scheme, making its purpose clear and unique among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context: 'Use for retiree regular-income planning.' Although it does not mention when not to use or list alternatives, the context is clear enough for an agent to decide when to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the high-level operation. It does not disclose underlying assumptions like compounding frequency or periodic nature of SIP, which are important for accurate use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences, no redundant information, and front-loaded purpose. Every word serves a clear function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple three-parameter calculation tool with an output schema, the description covers the main purpose but omits details like compounding frequency and edge cases. It is minimally adequate but could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only mentions parameter names in context without specifying units, formats, or constraints. For example, 'annual_return' could be a percentage or decimal, and 'target_amount' lacks currency context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates monthly SIP needed to reach a target corpus and explicitly calls it an inverse SIP calculation, distinguishing it from siblings like calculate_sip_returns which does the forward computation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a target amount and need the monthly investment, and the 'inverse SIP' phrasing hints at differentiation from forward SIP calculators, though it does not explicitly list alternatives or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 explains the formula and the concept of downside deviation, but does not disclose any behavioral traits such as input validation, handling of edge cases (e.g., zero downside deviation), or return format. For a simple numeric calculation, this may be sufficient but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences. The first states the formula and purpose, the second provides comparative context. Every sentence adds value without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is an output schema (though not shown) and no complex behaviors, the description provides the core information. However, it lacks explanation of potential errors (e.g., division by zero) and does not describe the return value structure. For a simple tool this is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It mentions the three parameters (portfolio_return, risk_free_rate, downside_deviation) by name in the formula, but does not explain their meaning, expected units, or typical ranges. This leaves ambiguity about what values to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the Sortino ratio using the formula (Rp - Rf) / Downside Deviation, and distinguishes it from the Sharpe ratio by noting it only penalizes downside volatility. This is a specific verb+resource with clear purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context by comparing to Sharpe ratio ('Like Sharpe but only penalizes downside volatility'), helping users decide when to use this tool. However, it does not explicitly state when not to use it or list alternative tools beyond the implicit comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the calculation is approximate and provides the formula. With no annotations, the description carries the burden and does well for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one sentence plus formula. Front-loaded with 'Rule of 72'. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity, single parameter, and presence of output schema, the description fully covers purpose and calculation method. No missing context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'annual_rate' in the formula, but does not specify if it's in percentage or decimal form. For a single parameter with 0% schema coverage, it adds basic meaning but could be more precise.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool approximates years to double money using Rule of 72, providing a specific verb and resource. It distinguishes from siblings by naming a unique financial rule.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like calculate_future_value or calculate_cagr. The description does not mention exclusions or context for choosing Rule of 72.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses that it adjusts for inflation and calculates SIP, but does not explain other behavioral traits such as assumptions about returns (expected_return default 12%), whether it accounts for taxes, or that it is a simulation without modifying real data. More transparency would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with goal types, then core actions. Every word adds value and there is no redundancy. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters, no schema descriptions, and no annotations, the description covers the main purpose and key actions (inflation adjustment, SIP calculation). The output schema exists, so return values are documented elsewhere. However, additional details on assumptions or edge cases would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only implicitly mentions target_amount_today, years_to_goal, inflation_rate, current_savings, and expected_return. It does not explain the role or format of each parameter, leaving the agent to infer from parameter names alone. The description should provide more detail to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Plan' and resource 'financial goal' with specific examples (education, house, car, wedding). It distinguishes from sibling tools by explaining it adjusts for inflation and calculates monthly SIP, which is a comprehensive planning action rather than a single calculation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for comprehensive goal planning with inflation and SIP, but does not explicitly mention when not to use it or list alternatives. Sibling tools like calculate_sip_needed or calculate_future_value are simpler, so the agent can infer context but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility. It discloses that it searches AMFI data and returns scheme codes. However, it lacks details on behavior such as pagination, error handling, rate limits, or whether it returns exact matches or fuzzy results. The description provides partial context but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that front-load the purpose and outcome, immediately followed by usage guidance. Every sentence earns its place, with no superfluous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (not shown, but indicated), the description does not need to detail return values. It adequately covers the search intent and lifecycle (before fetching NAV). Minor gap: does not explain that multiple schemes could match a query, but this is partially addressed by the intent of getting a code.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the schema itself does not describe parameters. The description does not explain the meaning of 'query' (the fund name) or 'limit' (max results) beyond their names in the schema. It fails to add value that helps the agent understand how to use the parameters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search'), the resource ('Indian mutual-fund schemes by name'), and the outcome ('get their scheme codes'). It uses a specific verb and resource, distinguishing it from siblings like get_mutual_fund_nav.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use the tool: 'Use when a user names a fund ... and you need its code before fetching the live NAV.' This provides clear context and implies when not to use (e.g., when you already have the code). No explicit exclusions or alternatives listed, but the use case is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It is a calculation tool with no side effects; the description adequately states what it does but does not elaborate on output format, error cases, or permissions. It is sufficient for a simple read-only calculation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences. The first sentence states the purpose, followed by the formula and an explanatory note. No redundant or filler text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculation tool, the description covers the purpose and formula. Since there is an output schema (context signal), the lack of output format description is acceptable. However, it could hint at the output type.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 0%, the description includes the formula E(R)=Rf+β×(Rm−Rf), which implicitly defines the three parameters (risk-free rate, beta, market return). However, it does not explicitly describe units or valid ranges.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Calculate expected return using CAPM', which is a specific verb and resource. It also provides the formula and explains beta implications (defensive vs aggressive), making the purpose clear and distinct from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The formula implies it is for CAPM calculations, but there is no mention of prerequisites or scenarios where other tools might be preferable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the formula and additional outputs, but does not mention assumptions (e.g., fixed rate, monthly compounding) or limitations. Still sufficiently transparent for standard use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The formula is included concisely, and key outputs are noted. Front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description does not need to detail return values. It covers the core function and additional metrics. Adequate for a financial calculation tool with siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameters are clearly named (principal, annual_rate, tenure_years) but the description adds little beyond naming the formula. It does not specify units (e.g., rate as decimal or percentage, tenure in months vs years) or constraints, despite 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates EMI for a loan, providing the formula and additional outputs like total interest and interest-to-principal ratio. It distinguishes from siblings such as loan_amortization and compare_loans.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives like loan_amortization or calculate_prepayment_savings. It implies usage for EMI calculation but lacks guidance on selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must convey behavioral traits. It specifies 'quarterly compounding', a key behavior. Since an output schema exists, the description does not need to detail return values, and no destructive or auth-related issues are expected for a calculation tool. The description is adequate but could mention other assumptions (e.g., interest reinvested).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two short sentences with no extraneous information. Every word adds value, making it efficient for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 required parameters, no nested objects, output schema present), the description is mostly sufficient but lacks detail on parameter specifics and potential edge cases (e.g., rounding of compounding). For a calculation tool in a large suite, a bit more context on how the result is computed (e.g., formula) could help, but the current version meets basic needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate by explaining parameter meanings or units. The term 'fixed monthly deposit' hints at 'monthly_deposit', and 'quarterly compounding' relates to 'annual_rate' and 'months', but no explicit mapping or additional details (e.g., that annual_rate is in percentage, months as integer periods) are provided. The parameter names are self-explanatory, but the description adds minimal value beyond that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates RD maturity for a fixed monthly deposit with quarterly compounding. It is specific to Recurring Deposits and includes usage context ('monthly bank RD maturity / interest'), effectively distinguishing it from sibling tools like calculate_fixed_deposit or calculate_sip_returns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a usage hint ('Use for monthly bank RD maturity / interest'), indicating when to apply this tool. However, it does not explicitly state when not to use it or mention alternatives among the many sibling calculators, which would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the data source (Yahoo Finance) and gives examples but does not disclose limitations like API rate limits, latency, symbol validity behavior, or data freshness. Minimal behavioral transparency beyond core function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences plus examples, with no wasted words. It front-loads the purpose and immediately provides illustrative examples, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema (not shown but present), the description adequately covers the function. It could be improved by briefly noting the response structure (e.g., price, change), but the output schema likely covers that. Given the tool's low complexity, completeness is high.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema defines 'symbol' as a required string with no description (0% coverage). The tool description compensates by providing concrete examples like '^NSEI' and 'RELIANCE.NS', which clarify the expected format. This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Live equity/index quote (Yahoo Finance)' with a specific use case 'current price/level of X' and provides concrete examples like '^NSEI' and 'AAPL'. It effectively distinguishes from siblings such as 'get_mutual_fund_nav' and 'get_fx_rate' which cover different asset types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies 'Use for 'current price/level of X'', giving clear usage context. However, it does not explicitly mention when not to use this tool or provide alternatives, though the sibling list implies boundaries against similar tools for mutual funds and FX.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that the tool is a pure mathematical calculation (PV = PMT/r, etc.), implying no side effects or destructive actions. Could mention assumptions like constant growth rate or precision, but the transparency is adequate for a simple financial function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is very short (two sentences plus formulas) and front-loaded with the purpose. Every sentence earns its place. Could be slightly improved by listing parameters more clearly, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple math), it covers the core purpose and formulas. Output schema is present (context says true), so description does not need to detail returns. Missing edge cases (e.g., growth_rate >= annual_rate) but otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description adds meaning beyond parameter names and types. It maps payment to PMT, annual_rate to r, growth_rate to g, and shows formulas. This clarifies that growth_rate is optional (default 0) for simple perpetuity. Adds significant value by explaining mathematical relationships.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('calculate present value') and clearly identifies the resource ('perpetuity'). It distinguishes from siblings like annuity and future value by explicitly stating 'infinite periodic payments' and providing formulas for simple and growing perpetuities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool over alternatives. It implies usage for perpetuities but lacks guidance on comparing to annuity or other time-value-of-money tools. The context of sibling tools provides implicit contrast, but the description could benefit from highlighting scenarios (e.g., 'Use for perpetual cash flows, not for finite annuities').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It discloses the scaling for three parameters (1-5) and required inputs, but could be more explicit about the non-destructive nature and output structure. Still adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose and inputs, second gives usage context and parameter scales. No fluff, front-loaded, and every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists (context signal), description need not detail return values. It covers all essential input factors and usage scenarios. Minor gap: no mention of output format, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, description adds value by explaining scaling for income_stability, investment_knowledge, loss_reaction, but does not mention the 'dependents' parameter. Partially compensates but not fully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool determines an investor's risk profile and suggests an equity/debt split based on multiple factors. The verb 'determine' and resource 'risk profile' are specific and distinct from sibling calculation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use the tool, e.g., 'Use when a user asks what kind of investor I am' or before recommending asset allocation. This provides clear context and differentiates from other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 deposits for 15 years, maturity in 21 years, and annual compounding, but does not disclose assumptions like constant interest rate or any limitations. This is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loading the purpose and key details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (not shown), the description covers the essential aspects: what is calculated, for whom, and the terms. It could be improved by noting the assumption of constant interest rate, but for a simple tool it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description explains deposit_years (15), maturity_years (21), and annual_deposit (implied). It does not explicitly describe annual_rate, though 'annual compounding' implies its existence. This adds significant meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool calculates Sukanya Samriddhi Yojana maturity for a girl child, specifying its use for daughter education/marriage savings. It clearly distinguishes from siblings like calculate_ppf by naming the specific scheme.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use (daughter education/marriage savings, SSY corpus) but does not explicitly mention when not to use or suggest alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It explains the formula (EV = Σ[FCF/(1+WACC)^t] + Terminal Value, Equity = EV - Net Debt) and gives an example input format. However, it does not describe the output structure or any assumptions/limitations, though an output schema exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, cleanly structured, and front-loaded with the tool's purpose. Every sentence adds value: naming the method, giving an input example, and stating the core formula.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description is nearly complete. It covers the key inputs and the valuation formula but could briefly mention how net_debt and shares_outstanding affect the result (e.g., per-share equity). The tool has 5 parameters, but the description focuses on the most critical ones.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It clarifies the format for free_cash_flows_json with an example array. It also mentions WACC, terminal growth, and net debt through the formula. However, net_debt and shares_outstanding are not explicitly explained, though their roles are implied by the formula.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Discounted Cash Flow (DCF) valuation', which is a specific verb+resource. It distinguishes this tool from sibling tools like value_stock_ddm, value_stock_pe, etc., which are alternative valuation methods.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that DCF is used for free cash flow based valuation, but it does not provide explicit guidance on when to use this tool versus alternatives like DDM or PE. No direct comparisons or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It details the steps (net worth, cash flow, emergency fund, etc.) and the canonical order. Lacks explicit mention of side effects or data persistence, but overall provides good behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single paragraph with front-loaded purpose, but it's somewhat lengthy. Every sentence adds value, though could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters, 3 required, and an output schema, the description covers the high-level process and output. It mentions the action plan components but lacks detail on output schema structure. Still fairly complete for a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It names required parameters (age, monthly_income, monthly_expenses) and implies others are optional via defaults, but does not explain each parameter's meaning or unit. Adds context but not full parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a holistic financial plan from a user's life situation, specifying input (plain language financial story) and output (prioritized action plan). It distinctly differentiates from siblings by being the 'best first tool' and chaining multiple analyses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'the best first tool when someone describes their finances in plain language' and advises to drill into specific calculators after. Provides clear when-to-use and suggests alternatives for detailed calculations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the model (cost-of-carry), formula, and use of dividend_yield. It does not cover assumptions or limitations, but it is transparent enough for an agent to understand the behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, front-loaded with the purpose, and every sentence adds value. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's financial complexity and the presence of an output schema, the description adequately covers the formula, usage context, and key parameters. It could mention edge cases but is sufficient for most agents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It mentions spot_price, annual_rate, years, compounding (default continuous), and dividend_yield, with explanation that dividend_yield is for stocks/indices. The formula ties parameters together, adding significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the fair value of a futures/forward contract using cost-of-carry, which is a specific verb-resource combination. It distinguishes itself from sibling tools like 'calculate_futures_hedge' by focusing on pricing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use when a user asks what should the futures/forward price be, about carry, contango/backwardation, or arbitrage-free pricing...' This provides clear context for usage, though it does not explicitly mention when to avoid using it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. Discloses formula, tax-exempt limit (₹20,00,000), and service requirement. Adds behavioral context beyond a simple calculation, though it doesn't mention edge cases like partial years.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences front-loaded with purpose, then usage, then details/formula. Every sentence adds unique value with no redundancy. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return value description is not required. Covers purpose, usage, formula, and constraints. Minor gap: no mention of behavior for tenure less than 5 years, but overall sufficient for a simple calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no descriptions), but the description mentions 'Last Salary' and 'Years' in the formula, mapping loosely to parameters last_monthly_salary and tenure_years. However, it does not explicitly define units or clarify that salary is monthly, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Calculate gratuity under India's Payment of Gratuity Act, 1972', specifying the verb (calculate) and resource (gratuity) with legal context. Distinguishes from siblings like calculate_future_value or calculate_epf by focusing on gratuity specifically.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use when a user asks about gratuity eligibility or payout at retirement/resignation' and adds condition 'Applies to employees with 5+ years of continuous service'. Provides clear when-to-use guidance without needing alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, but the description includes the exact formula (C - P = S - K×e^(-r×t)), making the calculation transparent. It does not disclose assumptions like European options, but given the absence of annotations, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with three sentences, no redundant words. The key formula is front-loaded, and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the moderate complexity and presence of an output schema, the description is complete enough. It covers the purpose, usage, and formula. Minor missing context about assumptions is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by explaining how to use the optional price parameters ('leave the other at -1') and provides the formula linking all parameters. This compensates for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'derive the fair call or put price, or detect arbitrage,' specifying the exact financial concept and outcomes. It distinguishes from siblings like calculate_option_payoff and calculate_black_scholes by focusing on put-call parity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent to 'Provide whichever option price you know; leave the other at -1 to solve it,' providing clear usage instructions. However, it does not mention when not to use or suggest alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full transparency burden. It specifies the data source (ECB via Frankfurter) and uses the term 'live', which implies near real-time data. However, it does not disclose update frequency, rate limits, or any caching behavior. This is adequate for a read-only lookup tool but could be more explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences. The first sentence states the core function and source. The second sentence provides use cases and a parameter format example. Every sentence adds value without redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description need not detail return values. It covers the source, usage, and parameter format. It misses details like error handling for invalid codes or rate limits, but for a simple lookup tool, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% coverage, meaning no descriptions for parameters. The description compensates by explaining that 'symbols can be comma-separated, e.g. INR,EUR,GBP' and implies base defaults to USD. It adds meaning beyond the bare schema, though it could explicitly state the expected ISO currency codes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool provides 'live currency exchange rates' using 'ECB reference, via Frankfurter'. It explicitly mentions use cases like 'what's the USD/INR rate', converting amounts, or FX-impact questions, making the purpose unambiguous and distinct from sibling tools that focus on financial calculations rather than real-time rates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear scenarios for using the tool (currency conversion, FX-impact questions) but does not explicitly state when not to use it or mention alternatives among the extensive sibling list. While the context implies it's for live rates only, lacking explicit exclusions prevents a top score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes the tool as retrieving 'latest live NAV', implying a read operation with near-real-time data. No side effects or limitations mentioned, but the activity is straightforward and the description is sufficient for such a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. First sentence states purpose, second provides usage context and a prerequisite. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter and an output schema, the description covers the essential usage: purpose and how to obtain the input. It could mention that the output is just the NAV, but the output schema handles that. Reasonably complete for a simple lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It refers to 'AMFI mutual-fund scheme code' and directs to search_mutual_funds, but does not add further detail about the parameter format or valid values. This is minimal compensation for the lack of schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves the latest live NAV for an AMFI mutual-fund scheme code using a specific verb+resource. It distinguishes from sibling search_mutual_funds by specifying that the scheme code must be found first.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states it is used for 'what's the current NAV of fund X', and instructs to first use search_mutual_funds to obtain the code. This provides clear context and a prerequisite.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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