AVnester — Indian Real Estate Intelligence

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

Annotations already declare readOnlyHint, idempotentHint, and not destructive. The description adds value by clarifying it is 'deterministic math; not advice or a loan-approval claim' and mentions the response includes assumptionNote and disclaimer, which goes beyond what annotations provide.

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 with 5 sentences, each serving a purpose (purpose, nature, usage modes, output hint). It is front-loaded with the main action and free of unnecessary 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?

Given the tool's complexity (4 parameters, output schema present), the description covers the two modes, mentions response fields (assumptionNote, disclaimer), and specifies geographic context (India). It is complete for an agent to correctly invoke this 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 baseline is 3. The description reiterates the mode distinction (propertyValue vs loanAmount) but adds no substantial new meaning beyond what the schema already explains about each parameter.

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

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

The description clearly states it estimates monthly home-loan EMI for India, using specific verbs like 'estimate' and defining resource as 'home-loan calculator'. It distinguishes from sibling tools by specifying it's for EMI calculation, not comparisons or other fees.

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 explicitly states when to use it ('what would my EMI be' / 'monthly payment on …') and explains the two modes (propertyValue or loanAmount). While it doesn't list when not to use or directly compare to siblings, the context is clear given the sibling names.

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?

Adds significant behavioral context beyond annotations: 'Pure deterministic math — no advice, no loan-approval claim' and 'Always surface the disclaimer field.' Annotations already indicate readOnly/idempotent/non-destructive; description enriches with operational constraints.

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?

Three sentences, front-loaded with purpose, no unnecessary words. Each sentence earns its place: purpose, usage guidance, and output summary with disclaimer note.

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?

Despite 6 parameters and required outputs, the description covers all key aspects: what it compares, when to use, what it returns (including disclaimer). Output schema exists so return values are further detailed; description provides sufficient high-level completeness.

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 each parameter is described in the schema. Description does not add further parameter details but summarizes outputs. Baseline score of 3 applies as description adds no extra parameter meaning.

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

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

Description clearly states it compares staying vs. transferring a home loan, lists what it returns, and explicitly says when to use it (user asks about switching/refinancing). Distinguishes from siblings like simulate_loan_prepayment.

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 explicit usage context: 'Use when the user asks...' and clarifies it is pure math with no advice/approval. Lacks explicit when-not-to-use or alternative tools, but context is sufficient.

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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by disclosing that out-of-scope cities return a specific signal (supported=false) and instructs to surface scopeMessage. It also hints at the output including specific dimensions. No contradictions.

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 4 sentences, front-loaded with core purpose, then usage guidelines, then edge case handling, then sibling differentiation. Every sentence serves a clear purpose 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?

Given full schema coverage, an output schema exists, and rich annotations, the description covers purpose, usage, behavioral quirks, and sibling differentiation completely. No gaps identified.

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 descriptions for all 3 parameters. The description adds extra guidance beyond schema: localities must be an array (not comma-separated) and city must cover all localities. This helps the agent construct valid inputs correctly.

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 ('Compare') and resource ('localities'), and lists concrete aspects (price trends, livability, investment grade, strengths, watchouts). It also explicitly distinguishes from sibling tool compare_properties, which handles listing IDs.

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 explicitly tells when to use (user asks 'X vs Y' or 'which is better') and handles out-of-scope cities (returns supported=false with scopeMessage). It also contrasts with compare_properties for listings, providing clear decision criteria.

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?

Annotations already provide readOnlyHint, idempotentHint, destructiveHint false. The description adds significant context: Coimbatore-only, handling unknown IDs, no purchase recommendation, and the disclaimer requirement. This goes beyond annotations without contradicting them.

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 paragraph of 5-6 sentences, front-loaded with the primary action. Every sentence adds necessary information without redundancy. Could be slightly more structured but remains concise and readable.

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 presence of an output schema (not shown but noted), the description covers edge cases (unknown IDs, >5 candidates, Coimbatore-only), behavioral notes (no recommendation, disclaimer), and mentions key return fields. It is comprehensive for a tool with a single parameter.

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 coverage is 100% for the lone parameter listingIds. The description adds value by mentioning that order is preserved in output, and that IDs are not guessable, requiring prior call to search_properties. This extends the schema documentation.

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

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

The description clearly states the tool compares 2-5 AVnester listings side-by-side by listingId. It distinguishes from siblings like search_properties (which provides IDs), compare_localities, and other comparison tools. Specifics like Coimbatore-only and return behavior for unknown IDs further clarify the scope.

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 explicitly tells users to get IDs from search_properties first, and provides guidance when there are more than 5 candidates (pick most relevant 5). It lacks explicit 'when not to use' but the context is clear.

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

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

Annotations already indicate readOnly, idempotent, openWorld, and non-destructive. Description adds behavioral details: handling of states outside India (supported=false), GST itemization based on constructionStatus, and buyer-gender concessions. No contradiction with annotations.

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

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

Four sentences, no wasted words. Front-loaded with purpose, then key features, special case, and disclaimer. Each sentence contributes meaning.

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 8 parameters, 100% schema coverage, and existence of output schema, the description covers main functionality, edge cases (supported=false for non-India), and offers a customer-facing disclaimer. Could mention rateBasis set but is implied. Complete 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 100%, so baseline is 3. Description adds value by explaining the effect of parameters (e.g., 'urban/rural overrides', 'commercial/agricultural multipliers') and provides a usage hint for constructionStatus to get GST. This goes beyond schema descriptions.

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 it estimates Indian state stamp duty and registration charges, using specific verb 'Estimate' and resource 'stamp duty + registration'. It distinguishes from siblings like calculate_home_affordability or compare_properties by focusing on statutory charges.

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?

Description provides context for usage (property purchase in India) and includes a disclaimer ('Always surface the disclaimer'), but does not explicitly state when not to use this tool or compare with alternatives among 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?

Annotations already indicate safe, idempotent read operation. Description adds key behaviors: out-of-scope cities return supported=false and to surface scopeMessage, and always surface disclaimer for grades. No contradictions.

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 cover purpose, data returned, usage context, and edge-case handling. Every sentence adds value; no fluff.

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

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

Given the tool's complexity (multiple fields, error handling, disclaimers) and the presence of an output schema, the description covers all critical aspects: return fields, usage trigger, and special handling. Could mention that city is restricted to supported Indian cities, but out-of-scope behavior covers that.

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 clear descriptions. The description adds that city is Indian and locality is within an Indian city, but this is already implied by schema patterns. No new semantic value beyond schema.

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

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

The description clearly states the tool aggregates insights for a Coimbatore locality, listing specific data points (avg price, supply count, etc.) and includes a usage trigger ('what is X locality like'). It effectively distinguishes from sibling tools by targeting single-locality queries.

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?

Explicitly tells when to use (user asks about a locality) and how to handle out-of-scope cities (surface scopeMessage) and disclaimers. Does not explicitly list when not to use or name alternatives, but the context is clear enough.

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?

Annotations already mark it as read-only, idempotent, and non-destructive. The description adds behavioral context: it is an assessment, not a loan approval, and always surfaces a disclaimer. It details the verdict categories and factors considered, providing value beyond annotations.

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

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

The description is concise at about 100 words, but information is densely packed. It could be improved by structuring into bullet points or separating modes. Front-loading is good, capturing the main purpose and verdict types.

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

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

Given the tool's complexity (21 params, two modes, multiple factors), the description covers the essential purpose, modes, verdict, and disclaimer. It does not need to explain output schema since it exists. Some assumptions (e.g., default self-occupied) are in parameter descriptions, not the main description, but overall it is adequate.

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 describes all parameters. The description adds value by explaining the interaction between parameters (e.g., listingId vs propertyValue+state modes), but does not add meaning to individual parameter 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 clearly states the tool assesses affordability of an Indian home, providing one of four verdicts, and distinguishes two modes (listingId vs propertyValue+state). It effectively separates from loan approval/advice. This differentiates it from siblings like calculate_home_affordability.

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 specifies when to use each mode and includes a disclaimer that it is not a loan approval. However, it does not explicitly guide the agent on choosing this tool over calculate_home_affordability or other siblings, missing a direct alternative comparison.

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

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses that unknown IDs return { listing: null, notFound: true } and never throw, to avoid leaking existence. This adds significant value.

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?

Three sentences, each with a specific purpose: the action, prerequisite/integration, and behavior/error handling. No unnecessary 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?

Covers when to use, prerequisite, error handling, scope (Coimbatore-only), and return format. For a simple fetch tool, it is 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 coverage is 100%, but the description adds context: IDs are not guessable, must call search_properties first, and the listingId is the trailing segment of a sourceUrl. This provides meaning beyond the schema's description.

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

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

The description clearly states the tool fetches full public details for one AVnester listing by listingId. It distinguishes itself from sibling tools like search_properties (which returns multiple results) and compare_properties (comparison).

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 explicitly says to get the listingId from search_properties results first and that it's the natural follow-up to a search. It also says 'Use when the user references a specific listing.' However, it does not explicitly mention when not to use, but the context is clear.

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

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

Annotations already indicate readOnlyHint, idempotentHint, openWorldHint, non-destructive. Description adds that it is pure deterministic math, not tax advice, and lists modelled sections and exclusions. No contradiction.

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?

Three sentences with no extraneous information. Front-loaded with core purpose, followed by usage guidance and behavioral notes. Every sentence serves a purpose.

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 18 parameters, output schema exists, and annotations provide safety signals, the description covers the essential behavioral aspects: what is modelled, what is excluded, disclaimer requirement, and usage triggers. Complete for the complexity.

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 full descriptions for all 18 parameters. The description does not add meaning beyond the schema for individual parameters, but it provides high-level context of what the tool computes. 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?

Description clearly states the tool compares OLD vs NEW tax regime for home-loan borrowers to recommend the cheaper one, using deterministic slab math. It distinguishes from sibling tools (none of which are tax calculators) by naming specific user queries and tax sections.

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?

Explicitly tells when to use: when user asks 'old or new tax regime', 'home-loan tax benefit', or 'section 80C / 24(b) deduction'. Lists what it does and does not model (capital gains, HRA, etc.), and reminds to surface disclaimer.

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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by detailing return format (sanitized listing cards, handoff URLs, verified flag) and constraints (never returns seller contact details, out-of-scope cities return supported=false with scopeMessage).

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, perfectly front-loaded: first sentence states purpose and scope, second sentence covers usage conditions and return behavior. 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?

Despite having 9 parameters, the description is complete given the full schema and output schema. It covers use case, error handling, and key return details. Minor gap: doesn't explicitly list all parameters, but schema covers them.

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 baseline is 3. The description mentions 'price band, BHK, or transaction type' but does not add new meaning beyond what the schema already provides for parameters.

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 it searches residential property listings in Coimbatore, Tamil Nadu, providing a specific verb and resource. It distinguishes itself from siblings like compare_properties and get_property_details by scoping to Coimbatore and specifying the search use case.

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?

Explicitly states 'Use when the user names a Coimbatore locality, price band, BHK, or transaction type.' It also explains out-of-scope behavior. However, it does not explicitly mention when not to use this tool versus alternatives for other cities, though no sibling covers that directly.

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?

Annotations already indicate readOnlyHint, idempotentHint, destructiveHint. The description adds context: 'Pure deterministic math — no advice, no loan-approval claim,' which clarifies the tool's non-advisory nature. No contradictions.

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 with no redundant sentences. Each part serves a purpose: stating the function, clarifying it's a calculator, listing use cases, and summarizing modes and strategies.

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

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

Given the tool's complexity (8 parameters, multiple modes), the description covers all key aspects: purpose, use cases, modes, strategies, and a usage instruction (disclaimer). An output schema exists, so return values need not be detailed.

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% (all parameters described). The description adds value by summarizing modes and strategies (e.g., 'Modes: one-time, recurring yearly...') and the comparison of reduce_tenure vs reduce_emi, which goes 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 clearly states the tool simulates prepaying an Indian home loan early, lists specific use cases (e.g., 'should I prepay'), and describes modes and strategies. It is distinct from sibling calculators like 'calculate_home_affordability'.

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 explicitly lists when to use the tool (e.g., 'use for early/part/lump-sum repayment') and instructs to 'always surface the disclaimer field.' However, it does not explicitly state when not to use or compare to alternative tools.

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