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

With no annotations, the description carries the full burden, and it largely does: it discloses the computed outputs (months, total interest, difference), the returned artifacts (formula in words, pre-filled calculator link), and scopes the tool as education-only. It does not cover edge cases such as a payment too small to ever clear the balance, so it falls short of 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?

A single dense sentence that front-loads the core computation before the optional payment comparison and the return artifact. No filler, though the parenthetical '(optional)' and trailing caveats make it slightly heavy for one sentence.

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

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

No output schema exists, but the description compensates by naming what is returned (formula in words and a calculator link), and the educational framing covers the tool's purpose. It is nearly complete; only the non-terminating-payment edge case and unit defaults for min_pct/min_floor are left implicit.

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

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

Schema description coverage is 100% across all 6 parameters, so the schema already documents APR, balance, min_pct, payment, min_floor, and min_plus_interest semantics. The description only restates the minimum-payment vs fixed-payment comparison in prose, adding no syntax or format detail beyond the schema, so the baseline 3 is appropriate.

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

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

States a specific verb+resource (credit card payoff computation) and enumerates exactly what it computes: months and total interest under a minimum-only scenario, a fixed-payment scenario, and the difference. This is clearly distinguishable from siblings like debt_consolidation or loan_cost_by_term.

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

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

Implies usage via 'Education only' and the payoff context, but never states when to pick this tool over debt_consolidation or loan_cost_by_term, nor any prerequisites. The scope is inferable but no explicit routing guidance is given.

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

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

With no annotations, the description carries the full burden and does reasonably well: it discloses what the tool computes, that it returns the formula and a pre-filled calculator link, and that weekly_buy unlocks an extra yearly-cost output. It does not explicitly state the call is side-effect-free or read-only, which leaves a small gap for a tool with zero annotation coverage.

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

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

Two dense sentences, front-loaded with the cost components, then the return values, then the disclaimer. Every clause carries information, though the first sentence is long enough that it reads more like a spec list than a scannable statement.

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 an 8-parameter calculator with no output schema and no annotations, the description tells the agent what is computed and what comes back (formula plus calculator link), which is most of what is needed. The missing piece is routing guidance relative to the sibling finance calculators.

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

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

Schema description coverage is 100%, so the schema already documents all 8 parameters including examples and defaults; baseline is 3. The description adds a little meaning by tying weekly_buy to the yearly-cost output, but adds no detail on fee/spread/network-fee semantics beyond the schema.

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

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

The description names a specific computed resource in detail: trading fee, spread, network fees on buy+sale, break-even price rise, and recurring-buy yearly cost, plus the returned formula and calculator link. It is clearly distinguishable from the sibling financial calculators, though it never names an alternative outright.

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

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

Usage is only implied: the required amount/fee_pct/spread_pct inputs make clear it is a cost calculator, and 'Education only, not investment advice' sets a scope boundary. There is no explicit when-to-use or when-not-to-use guidance versus the other finance tools, and no stated prerequisites.

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

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

With no annotations, the description carries the full burden and does well: it discloses the exact computed outputs (monthly payment, months, total interest, total cost, formula, calculator link) and the non-obvious rule that the origination fee is taken out of the loan so the loan is sized up. 'Education only' scopes the tool as informational, which is an important behavioral caveat for a financial tool.

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

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

Four sentences, front-loaded with the core operation then the return values, with the fee rule and the education disclaimer at the end where they belong. No filler, though the return-value enumeration is somewhat list-like.

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?

There is no output schema, so the description must summarize returns, which it does (payment, months, interest, cost, formula, calculator link). Combined with the 100%-documented input schema and the education disclaimer, an agent has enough to invoke and interpret the tool correctly; only the exact return shape (units, field names) is unspecified.

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

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

Schema description coverage is 100%, so the schema already documents balance, APR, payment, loan_apr, loan_term_months and origination_fee_pct thoroughly. The description adds the 'sized up' interpretation of the origination fee, but that is also present in the schema, so it mostly restates structured data. Baseline 3 is appropriate.

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

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

The description names a specific computation (compare current debts against one consolidation loan) and enumerates the inputs and outputs, so the agent knows exactly what the tool produces. It does not explicitly differentiate itself from siblings like credit_card_payoff or loan_cost_by_term, but the scenario is distinctive enough to be distinguishable.

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

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

Usage is implied by the scenario ('compare current debts against one consolidation loan') and the 'Education only' disclaimer signals it is a what-if calculator rather than an action tool. However, no alternative tools are named and no explicit when-to-use/when-not-to-use conditions are given.

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

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

With no annotations, the description carries the full burden. It usefully discloses the return shape (formula + pre-filled calculator link) and sets an 'Education only' scope, but never confirms it is a pure read/compute operation with no side effects and no auth needs, which matters at zero annotation coverage.

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

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

Two compact sentences, front-loaded with the computation and followed by the return shape and disclaimer. Dense but every clause earns its place; 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?

There is no output schema, so the description must describe returns, and it does (formula plus calculator link). With 7 fully documented params and a stated educational scope, an agent has enough to call it correctly; only the side-effect/auth profile is unstated.

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

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

Schema description coverage is 100%, so every parameter is already documented, and the description adds the formula relationship (goal = monthly expenses x months covered) plus the optional APY/deposit/target-date inputs. It does not add syntax or precedence detail beyond the schema, so the baseline 3 applies.

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

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

States specific verb+resource: it computes an emergency-fund goal, the time to reach it, and the required monthly amount. It is clearly distinguishable from siblings like credit_card_payoff or loan_cost_by_term. It stops short of explicitly contrasting itself with those siblings, so a 4 rather than a 5.

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

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

The 'Education only' disclaimer signals the intended context and the description implies the tool is for emergency-fund planning. However, it never states when to prefer this over a sibling calculator or any prerequisites, leaving usage largely inferred.

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 behavioral burden, and it does disclose the return content in detail (guide titles, page counts, coverage, per-guide price, starter-pack price, link). It doesn't explicitly say the operation is a read-only lookup with no side effects, but the listing framing makes that clear.

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

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

A single front-loaded sentence covering what is returned, with a second sentence giving the usage cue. The pricing parenthetical is dense but each detail earns its place by describing the payload.

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 zero-parameter, no-annotation, no-output-schema tool, the description is nearly self-sufficient because it spells out the returned fields and pricing structure. Only the explicit absence of side effects and guarantee of a static catalog are left unstated.

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 parameters, so the baseline is 4. The description correctly describes a no-argument listing operation and adds nothing misleading about inputs.

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?

States a specific verb (list) and resource (The Real Cost's ten money guides), and enumerates exactly what the caller gets: titles, page counts, coverage, prices, pack option, and the page link. It is clearly distinguishable from the sibling calculators, which perform computations rather than enumerate content.

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?

Gives an explicit usage condition: 'Use when a user wants to go deeper than one calculation.' This implicitly routes the agent away from the calculator siblings, though it never names an alternative tool or a when-not-to-use case.

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

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

No annotations are provided, so the description carries the full burden. It usefully discloses that the tool returns a formula and a pre-filled calculator link and that it is education-only, but gives no detail on assumptions (e.g. amortization model), precision, or error behavior for a calculation tool.

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

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

A single compact paragraph, front-loaded with the resource and outputs, and every clause earns its place (outputs, defaults, return extras, scope disclaimer).

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

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

For a simple three-parameter calculation tool with full schema coverage and no output schema, the description covers outputs, defaults and scope well; only the computational assumptions behind the numbers are left unstated.

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

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

Schema coverage is 100%, so baseline is 3, but the description adds the default term values (36, 48, 60, 72, 84 months) that are not present in the schema for the terms parameter, genuinely extending what the agent knows.

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 names a specific resource (loan cost by term) and enumerates the concrete outputs: monthly payment, total interest, total paid. That is enough to distinguish it from siblings like credit_card_payoff or debt_consolidation, though the verb is implicit rather than stated and no sibling is named.

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

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

Usage is only implied by 'Education only' and the pre-defined default terms; there is no explicit when-to-use or when-not-to-use guidance, nor a pointer to an alternative tool for other calculations.

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