precisioncalc-mcp

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

With no annotations, the description carries the full burden and does disclose a key behavioral trait: 'One failure never aborts the batch,' indicating partial-failure isolation. It also mentions the 'max 100' limit. This is good but could further describe error reporting or output behavior, so not a 5.

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

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

The description is three compact sentences, front-loading the purpose ('Run many calculations') and then covering the parameter structure and failure behavior without any fluff. Every sentence earns its place.

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

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

The description covers the essential input contract and a key behavioral guarantee, but it omits what the response looks like (e.g., how results or errors are returned). Given the absence of an output schema and annotations, this is a minor gap for a batch tool, but it remains largely complete.

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

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

The schema only says 'calls' is an array of objects, but the description specifies each element as '{tool, arguments}' and adds the limit of 100. This is crucial semantic detail that compensates for the 0% schema description coverage.

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

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

The description clearly states 'Run many calculations in one request,' identifying the tool as a batch wrapper for calculation operations. This distinctively separates it from sibling tools like calculate_metric or currency_convert, which handle individual calculations.

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

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

The phrase 'Run many calculations in one request' implies consolidation of multiple calculation calls, and the 'PAID FEATURE' label signals a cost consideration. However, it does not explicitly name alternatives or exclude single-call usage, so it lacks a 5-level explicitness.

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

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

With no annotations, the description carries the full burden. It discloses that weekends and regional holidays are honored, and that count_business_days is inclusive. However, it does not specify return types (date string vs integer count) or the default region behavior, leaving ambiguity for the agent.

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

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

The description is compact and information-dense, but the run-on format with pipes and inline requirements makes it slightly dense and harder to scan. Still, it communicates a lot in few words without redundancy.

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

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

This is a complex tool with six parameters and multiple operations, no output schema, and no annotations. The description covers operations, required parameters, and holiday formatting well, but lacks examples, return value descriptions, and edge-case behavior (e.g., invalid dates), leaving it almost complete but not fully self-contained.

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

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

The schema has zero parameter descriptions, and this description fully compensates: it explains the role of operation, days (negative allowed), end_date (inclusive), region options, and custom_holidays format. Every parameter is meaningfully described.

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

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

Description clearly states the tool performs 'Business-day arithmetic honoring weekends + regional holidays' and enumerates specific operations (add, count, next, previous). This unambiguously distinguishes it from sibling tools like currency_convert 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.

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

Provides clear context on usage: it is for business-day calculations. It also details operation-specific requirements (e.g., add_business_days needs days, count_business_days needs end_date). However, it does not explicitly mention alternative tools or conditions when this tool should not be used.

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

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

With no annotations provided, the description carries the behavioral-disclosure burden. It usefully adds that calculations use 'exact decimal precision' and that rates/margins are decimals (0.05=5%). However, it does not disclose return format, error handling, currency behavior, or what happens with invalid metric names.

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

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

The description is two sentences, front-loaded with the core action and precision detail, followed by a compact colon-separated metric list and a single pointer to list_metrics. Every sentence earns its place with no wasted words.

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

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

The tool has a nested params object, no output schema, and no annotations, yet the description omits return values, param object details, and metric-specific inputs. The pointer to list_metrics is helpful but shifts essential schema information elsewhere, leaving this description incomplete on its own.

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

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

Schema description coverage is 0%, so the description must compensate. It adds the list of valid metric values and the decimal convention, which is helpful, but it does not explain the 'params' object structure or the 'currency' parameter; it merely defers to list_metrics instead of providing the needed semantics.

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

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

The description opens with a clear verb and resource ('Compute a business/SaaS/finance metric') and enumerates 14 specific metric names, making the tool's scope obvious. It does not explicitly contrast with sibling batch_calculate, but the listed metrics and exact-precision note sufficiently distinguish it from generic calculation tools.

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

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

The description implies usage for the listed metrics and instructs the agent to 'Call list_metrics for schemas,' which is useful navigation but not a true when-to-use statement. It does not mention alternatives such as batch_calculate or state when not to use this tool.

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

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

With no annotations provided, the description carries the transparency burden. It adds important behavioral details like the rate being an annual decimal (0.08=8%) and the valid compounding frequencies from daily to continuous. It does not describe the return value shape or edge-case behavior, but the core calculation semantics are disclosed.

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

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

The description is a single, dense sentence that front-loads the operation syntax and then provides key conventions. Every clause adds useful information with no filler.

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

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

Given the tool's 9 parameters and no output schema, the description is fairly complete: it maps operations to their arguments, explains rate decimal format, and lists compounding frequencies. It lacks details about currency meaning and return format, leaving minor ambiguity, but the main invocation path is clear enough.

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

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

Schema coverage is 0%, and the description compensates well by defining which parameters belong to which operation and by explaining rate units and compounding options. It covers most parameters, but omits any explanation of the currency parameter, which is a gap.

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

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

The description clearly states that this tool performs compound-interest/growth math and enumerates three specific operations (future_value, present_value, cagr) with their argument lists. This distinguishes it from sibling tools like internal_rate_of_return and net_present_value.

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

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

The description provides clear context by showing exactly which operation to use and which parameters each operation expects, e.g., 'operation: future_value (rate, years, present_value)'. However, it does not explicitly mention when to avoid this tool in favor of a sibling such as loan_amortization or depreciation.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals Decimal precision, the static offline table on the free tier, and the paid requirement for live/historical rates. This adds meaningful context about data freshness and accuracy, though it does not cover possible errors 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.

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

The description is two sentences, front-loaded with the primary action, and every phrase adds value. It covers scope, precision, and usage constraints without unnecessary fluff.

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

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

Given five parameters, no output schema, and no annotations, the description provides a high-level overview but leaves ambiguity about how date and live combine, what the returned result looks like, and any error conditions. It is adequate for a simple conversion tool but not fully complete.

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

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

Schema description coverage is 0%, so the description must compensate. It lists supported currencies, which informs value choices for from_currency and to_currency, and hints at the date/live interaction. However, it does not explicitly explain the formats or semantics of amount, date, or live, leaving some guesswork for the agent.

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

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

The description clearly states the tool converts amounts between major currencies, listing specific currency codes and noting Decimal precision. This distinguishes it from sibling financial calculation tools, which cover unrelated operations like batch calculations and net present value.

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

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

The description provides clear context about when to use the free tier versus the paid plan, mentioning static offline tables for basic conversions and live/historical ECB rates requiring a paid plan. While it doesn't explicitly name alternatives, the distinct scope of the tool makes usage straightforward, and the tier distinction guides decisions.

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

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

There are no annotations, so the description carries the full burden for behavioral disclosure. It adds the useful detail that 'Book value converges to salvage_value,' but it does not disclose the output format, rounding behavior, or how currency and useful_life_years affect the schedule.

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

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

The description is brief and front-loaded with the tool's purpose, and the two sentences contain no filler. However, the inline method list is somewhat terse and could be structured more clearly for readability.

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

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

For a financial calculation tool with no output schema and no annotations, the description is underspecified. It fails to state what a returned schedule looks like, whether output is per period, and how parameters like currency or useful_life_years are applied. This leaves significant ambiguity for an agent invoking the tool.

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

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

Schema description coverage is 0%, so the description must compensate for the lack of parameter documentation. It documents the allowed method values and links salvage_value to the end-of-schedule book value, but cost, useful_life_years, and currency are not explained at all. This is insufficient for a 5-parameter tool.

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

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

The description identifies the tool as an 'Asset depreciation schedule' and enumerates supported methods, which clearly distinguishes it from sibling tools like loan_amortization or compound_growth. However, it lacks an explicit verb such as 'calculates' and does not explicitly state the scope of the returned schedule.

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

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

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or appropriate context. The name and method list imply use for asset depreciation, but there are no explicit decision criteria or exclusionary instructions.

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

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

No annotations are present, and the description carries the full burden of behavioral disclosure. It fails to mention what the tool returns, whether it makes network calls, or any other operational behavior, offering no transparency.

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

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

The description is extremely brief but not in a useful way. 'Server health/status metadata' simply rephrases the tool name without adding informative content, making it under-specified rather than concise.

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

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

Given no output schema and no annotations, the description should explain what the health check provides (e.g., status codes, metrics, latency). It does not, leaving the tool's purpose and return value completely unexplained.

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

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

With zero parameters, the schema is already complete for parameter definition. The description need not add parameter details, and the baseline of 4 is appropriate.

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

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

The description 'Server health/status metadata' is vague and nearly tautological, restating the tool name 'health_check' without specifying a concrete action. It does not clearly differentiate from sibling tools beyond being non-calculation-related.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions, leaving the agent without direction.

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

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

Without annotations, the description provides some behavioral detail: it uses Newton + bisection and requires a sign change. But it does not disclose potential error conditions, the return value format, or whether it is a pure calculation, leaving gaps in behavioral understanding.

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

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

The description is concise and front-loaded, with the core definition appearing first. It consists of two short sentences that provide efficient context without unnecessary verbosity.

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

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

For a financial tool with two parameters, no annotations, and no output schema, the description is incomplete. It does not detail the cashflow array structure, the meaning of a sign change, the role of the guess parameter, or what the tool returns, making it insufficient for an agent to use confidently.

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

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

Schema description coverage is 0%, so the description must compensate for parameter meaning. It only indirectly mentions cashflows via the sign-change note and completely omits the 'guess' parameter, leaving both parameters poorly specified.

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

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

The description clearly states the tool computes an internal rate of return, defined as the per-period rate where NPV equals zero. This is a specific financial calculation and distinguishes it from siblings like net_present_value, though it does not explicitly contrast them.

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

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

It implies usage by stating a prerequisite: a sign change in cashflows is required. However, it does not explicitly mention when to use this versus alternatives like net_present_value, nor any conditions for avoiding it.

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

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

With no annotations, the description carries the full burden. It accurately indicates a read-only operation via the verb 'list' and specifies the contents of the returned list. It does not mention edge cases like empty lists or pagination, but for a simple catalog tool 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.

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

The description is a single concise sentence that directly states the tool's purpose and output content with no wasted words. It 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.

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

Given the tool's simplicity (zero parameters, no output schema, no annotations), the description fully covers what an agent needs: what it lists and what information is included. Sibling tools are all calculators, making the role unambiguous.

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

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

The tool takes zero input parameters, so the baseline is 4. The description's mention of 'required/optional params' refers to the output metadata for each metric, not the tool's input, and adds no ambiguity.

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

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

The description uses the specific verb 'list' and clearly identifies the resource as 'every supported metric,' which distinguishes it from calculation-related siblings. It also details the output content (descriptions and required/optional params), making the purpose unmistakable.

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

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

The description implies the tool is for discovering available metrics and their parameters. While it does not explicitly name alternatives or state when not to use it, the context of sibling tools (all calculations) makes it clear this is the discovery tool. A 4 is given because context is clear, but exclusions are not spelled out.

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

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

No annotations are provided, so the description carries the full disclosure burden. It reveals the payment formula and mentions the optional schedule, which is helpful. Yet it omits behavioral details such as handling of zero/negative interest rates, effects of extra_payment, rounding, or output structure.

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

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

The description is two sentences long and front-loads the main outputs. The formula is efficient and adds value without redundancy. Every word earns its place.

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

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

The core calculation is well-covered, but the tool has 6 parameters, no output schema, and no annotations. Missing details about extra_payment behavior, currency handling, and the exact shape of the amortization schedule leave notable gaps for a financial tool.

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

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

With 0% schema coverage, the description must explain parameters. It explains the three required parameters (principal, annual_rate, term_months) through the formula, but ignores currency, extra_payment, and include_schedule. This partial compensation is adequate for core use but incomplete for full understanding.

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

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

The description clearly identifies the tool as computing monthly payment, total interest, payoff, and an optional full schedule for a level-payment loan. It distinguishes from siblings by specifying the exact financial calculation and formula, making it unambiguous.

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

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

The phrase 'Level-payment loan' and the formula establish clear context for when to use this tool (fixed-rate, equal installment loans). However, it does not explicitly mention alternatives or exclusion scenarios, so it stops short of full when/when-not guidance.

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

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

With no annotations, the description carries the full transparency burden. It fully discloses the calculation formula and the sign/index convention for cash flows, which is strong behavioral transparency. However, it does not mention edge cases, rate period assumptions, or how currency affects the output.

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

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

Two sentences pack the formula and the critical period-0 convention with zero redundancy. Every element earns its place.

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

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

For a simple calculation, the core math and a key input convention are covered, but the missing semantics for 'currency' and lack of any stated return value leave gaps, especially since there is no output schema.

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

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

The schema has 0% description coverage, so the description must compensate. It explains cashflows indexing and rate's role in the formula, but the currency parameter is entirely unexplained, leaving a gap in parameter semantics.

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

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

The description clearly identifies the tool as computing Net Present Value via the explicit discounted cash flow formula, which distinguishes it from siblings like internal_rate_of_return and compound_growth. The formula and cashflows[0] convention make the tool's purpose unmistakable.

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

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

The description provides an important usage constraint by noting cashflows[0] is period 0 (usually the negative outlay), but it does not state when to prefer NPV over alternatives like IRR or compound growth, nor any exclusions or prerequisites.

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