homeloanscalculator

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

With no annotations, the description carries the full burden: it does disclose the core input-output relationship (income, EMIs, rate, tenure → max EMI and loan amount), which is the main behavioral fact. It does not state that this is a pure/read-only computation, nor does it address what happens when both months and years are supplied or how defaults are applied.

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 tight sentences: purpose first, then a compact illustrative example. Every part earns its place, though the example is borderline redundant given 100% schema coverage.

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

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

No output schema exists, and the description does name the two return values, so an agent knows what comes back. For a 6-parameter calculator, the remaining gaps (foir semantics, tenure conflict handling, defaulting behavior) are modest but real.

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 the baseline is 3, and the description adds value with a concrete example input that grounds units and magnitudes (rupees, percent, years). It still does not explain the foir parameter or the months-vs-years precedence, so it does not fully compensate for that 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 names a specific verb (returns), the computation (maximum EMI and home loan amount a borrower qualifies for), and the inputs it consumes. It is clearly distinguishable from siblings like emi or sensitivity by its qualification/eligibility framing, though it never names those siblings explicitly.

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 phrase 'maximum EMI and home loan amount a borrower qualifies for,' so an agent can infer this is the eligibility/affordability calculator rather than a plain EMI tool. However, there is no explicit when-to-use versus emi or sensitivity, and no mention of prerequisites or how it relates to the other siblings.

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

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

With no annotations, the description carries the burden well by disclosing that it supports optional prepayments and rate changes and that it returns EMI, total interest, and a yearly schedule. It omits edge-case behavior (e.g. if both years and months are supplied, rounding/precision) and has no output schema, so a minor gap remains.

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 well-formed sentences: the first front-loads inputs and outputs, the second gives a concrete example. Efficient with little waste; slightly dense but appropriately sized for a 9-parameter tool.

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

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

Given 9 parameters, nested objects, no annotation coverage, and no output schema, the description supplies the key behavioral shape (inputs, optional features, returns) and an example. It stops short of covering precedence rules and failure modes, but overall it is complete enough to invoke 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 100%, so the schema already documents every parameter including enums and nested objects, establishing a baseline of 3. The description reinforces this by naming prepayments and rate change and providing a concrete example input, but adds no 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?

States a specific calculation ('returns the monthly EMI, total interest and year-by-year schedule') on a specific resource domain (Indian home loan), which is clearly distinct from siblings like sensitivity or eligibility. It does not explicitly name or differentiate itself from those siblings, keeping it at 4 rather than 5.

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

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

The description implies the tool's role (compute EMI given loan parameters) but gives no explicit when-to-use/when-not guidance and never mentions alternatives such as sensitivity, which plausibly also computes EMI variants. Usage is inferable but not steered.

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 the core behavior (per-step recomputation of EMI and total interest) and supplies a concrete input example, but says nothing about what happens when 'deltas' is omitted, whether a default step grid applies, or the shape of the returned comparison.

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

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

Two sentences, front-loaded with the computation and followed by a compact literal example. Every element earns its place; only the example's redundancy with the schema keeps it off a 5.

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, and the description only broadly names the return values without indicating structure (per-delta rows, units, sign convention). For a 5-parameter analysis tool it is adequate but leaves the response shape ambiguous.

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%, including ranges and the 'give months or years' hint, so the schema does the heavy lifting. The description's example pins three of the five fields but adds no meaning for 'deltas', the parameter most likely to be misused.

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 computation: takes principal, annual rate and tenure, and returns how EMI and total interest shift as the rate moves in small steps. That distinguishes it in substance from the plain 'emi' sibling, though no sibling is named explicitly.

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 when-to-use is only implied by the word 'sensitivity' and the worked example; there is no statement of when to prefer this over 'emi' or of any preconditions. An agent can infer the scenario but must do the inference itself.

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

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

No annotations exist, so the description carries the burden. It does disclose the output shape (duty, registration fee, cess, total), which is valuable, and the 'takes... returns' framing implies a stateless computation. It does not explicitly state that it is read-only/pure, nor flag rate-assumption or rounding behavior.

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

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

Two sentences with the outputs front-loaded before the example input, zero filler. The example is slightly redundant against a 100%-covered schema but earns its place as a quick call template.

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

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

With no output schema, the description correctly enumerates the returned fields, which is what an agent needs to use the result. The minor gap is not clarifying the 'state rate row' vs slug discrepancy and not stating optionality of gender.

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 the schema already defines all three parameters, and a baseline of 3 applies. The worked example adds practical value, but the phrase 'a state rate row' conflicts with the schema's 'state slug' string parameter, creating a small ambiguity about what to pass.

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

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

The description uses a specific verb ('takes... returns') and names the exact domain resource: stamp duty, registration fee, cess and total for a property purchase. This clearly separates it from siblings like emi or taxBenefit, though it never names those siblings explicitly to reinforce the routing.

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 'for a property purchase' and the return fields, so an agent can infer the calculator context. However, there is no explicit statement of when to use this versus emi/sensitivity/taxBenefit, and no prerequisites or exclusions 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?

No annotations, so the description carries the full burden. It usefully discloses that output is per-repayment-year (not cumulative) and names the deduction categories, but never states this is a pure read-only computation with no side effects, nor how tenure is resolved when both years and months are supplied.

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, purpose front-loaded before the example, zero filler. The example input is compact and directly useful for invocation.

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

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

With no output schema, the description names the returned concepts but not their structure or field names, and leaves the years/months interaction and default year handling to the schema. Adequate to call, but thin for parsing results.

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% with unit and range descriptions for every parameter, so baseline is 3. The example input reinforces conventions (0.3 fraction, 8.5 percent) but adds little beyond what the schema already documents.

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 computation: takes loan amount, rate, tenure, slab and returns Section 80C and 24(b) deductions plus tax saved for a repayment year. Clearly distinguishable from siblings (emi, eligibility, stampDuty, sensitivity) by its tax-output focus, though it doesn't explicitly name a sibling.

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 input/output mapping, but there is no explicit when-to-use/when-not guidance and no routing against alternatives like emi or sensitivity. An agent must infer selection from intent alone.

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