UK Property Data

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns 'a list of matches' which provides basic output information, but doesn't describe pagination behavior, rate limits, authentication requirements, or what fields are included in the matches. The description adds some value but leaves significant behavioral aspects unspecified.

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 efficiently structured with a clear purpose statement first, followed by usage guidance, then parameter documentation. Every sentence earns its place by providing essential information without redundancy. The formatting with clear sections enhances 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 search tool with no annotations and no output schema, the description provides good context about purpose, usage, and parameters. However, it doesn't describe the structure of returned matches or potential limitations (like result count limits). Given the complexity level, it's mostly complete but could benefit from more detail about the output format.

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 description coverage for the single parameter, the description fully compensates by clearly explaining the 'query' parameter's purpose ('Company name to search') and providing concrete examples ('Tesco', 'Rightmove plc'). This adds essential meaning beyond what the bare schema provides, making the parameter's usage clear.

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's purpose with a specific verb ('Search') and resource ('Companies House by company name'), and distinguishes it from a sibling tool (read_resource) by explaining it's for name-based search rather than direct lookup by company number. This provides excellent differentiation from alternatives.

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 provides when-to-use guidance by stating this is for searching by company name and when-not-to-use guidance by directing users to read_resource for direct lookups by company number. It names the specific alternative tool and provides a concrete example of the alternative usage pattern.

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 full burden and does well by disclosing key behavioral traits: it returns specific data (council name, planning system type, direct URL), explains limitations (scraping is blocked), and provides guidance on next steps (use the direct_search link). It doesn't mention rate limits or authentication needs, but covers the essential operational context.

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?

Perfectly structured with purpose first, then return values, limitations, usage guidance, and parameter details. Every sentence earns its place with zero wasted words, making it easy to scan and understand quickly.

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 single-parameter tool with no annotations or output schema, the description provides excellent context about what it does, what it returns, and its limitations. The only minor gap is not explicitly describing the return format structure, but given the tool's straightforward nature, this is acceptable.

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 description coverage for the single parameter, the description fully compensates by providing the parameter name ('postcode'), its purpose ('UK postcode'), and clear examples ('e.g. "S1 1AA", "SW1A 2AA"'). This adds complete meaning beyond what the bare schema provides.

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 specific action ('Find the planning portal URL') and resource ('for a UK postcode'), distinguishing it from sibling tools like property_search or company_search by focusing on planning portal discovery rather than property or company data.

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 when NOT to use this tool ('Does NOT return planning application data — scraping is blocked by council portals') and provides an alternative action ('Use the returned search_urls.direct_search link to browse applications manually'), clearly differentiating it from potential data-scraping tools.

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 full burden of behavioral disclosure. It explains the search functionality and provides examples, but doesn't mention important behavioral aspects like rate limits, authentication requirements, error conditions, or what happens when multiple filters are combined. It also doesn't describe the return format or pagination 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?

The description is efficiently structured: a clear purpose statement, two usage examples, then organized parameter documentation. Every sentence serves a purpose - no wasted words. The information is front-loaded with the most important details first.

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 search tool with 10 parameters and no annotations or output schema, the description does an excellent job explaining parameters and usage. The main gap is the lack of information about return format, error handling, and system constraints. However, given the parameter complexity, it provides substantial context for effective tool selection.

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 description coverage for 10 parameters, the description fully compensates by providing detailed parameter documentation. Each parameter is clearly explained with examples (e.g., 'UK postcode (e.g. "SW1A 1AA") - required for postcode search'), format specifications ('ISO format'), and practical guidance ('default 25'). This adds substantial value beyond the bare 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's purpose: 'Search Land Registry transactions by postcode, address, date range, or price.' It specifies the verb ('search'), resource ('Land Registry transactions'), and search criteria, distinguishing it from sibling tools like property_epc or rental_analysis which serve different purposes.

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 explicit usage examples: 'Use for specific property history ("what has 10 Downing Street sold for?") or filtered market queries ("all sales over 500k in SW1 last year").' These concrete scenarios clearly indicate when to use this tool versus alternatives like property_comps or stamp_duty.

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 discloses behavioral traits such as grouping transactions by building and identifying sales patterns, but lacks details on permissions, rate limits, or response format. It adds context about what the tool does (e.g., 'identify blocks being sold off') but does not fully cover behavioral aspects like error handling or data sources.

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 appropriately sized and front-loaded, starting with the core purpose, followed by elaboration, and ending with parameter details. Every sentence adds value without redundancy, making it efficient and easy to scan.

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 complexity (3 parameters, no annotations, no output schema), the description is moderately complete. It explains the tool's purpose and parameters well but lacks details on output format, error cases, or integration with sibling tools. For a tool with no structured support, it should provide more behavioral and output context to be fully helpful.

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 provides clear semantics for all three parameters: 'postcode' as a UK postcode, 'months' as a lookback period with default, and 'min_transactions' as a minimum sales threshold with default. This adds meaningful context beyond the bare schema, though it could include examples or constraints for postcode format.

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's purpose: 'Find buildings with multiple flat sales — block buying opportunities.' It specifies the verb 'find' and resource 'buildings with multiple flat sales,' distinguishing it from sibling tools like property_comps or property_report by focusing on grouping transactions to identify investor exits and bulk-buy opportunities.

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 context by mentioning 'block buying opportunities' and 'investor exits,' suggesting it's for identifying bulk sales. However, it does not explicitly state when to use this tool versus alternatives like property_comps or ppd_transactions, nor does it provide exclusions or prerequisites, leaving some ambiguity.

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 full burden and does an excellent job describing behavioral traits: auto-escalation logic, EPC enrichment details (floor area, price/sqft, EPC rating), area-level statistics (median price/sqft, EPC match rate), and the percentile rank feature. The only minor gap is lack of explicit mention about permissions or rate limits.

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?

Perfectly structured with a clear purpose statement upfront, followed by key behavioral features, then a well-organized Args section. Every sentence adds value with no redundancy. The description is comprehensive yet efficiently organized.

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 complex tool with 8 parameters, 0% schema coverage, and no output schema, the description does an excellent job covering purpose, behavior, and parameters. The only minor gap is lack of explicit information about return format/structure, though the enrichment details provide some indication. Given the complexity, this is highly 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?

With 0% schema description coverage, the description fully compensates by providing detailed parameter explanations in the Args section. Each parameter gets clear semantics: postcode format examples, months as 'lookback period', limit as 'max transactions', search_level context, address purpose, property_type codes, enrich_epc details, and auto_escalate behavior with use case.

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 retrieves 'Comparable property sales from Land Registry Price Paid Data' and elaborates on the specific functionality including auto-escalation and EPC enrichment. It distinguishes itself from sibling tools like 'ppd_transactions' by focusing on comparable sales analysis with enrichment features.

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 explicit guidance on when to use specific parameters: 'usually leave as default' for search_level, 'Set false to keep results local — useful when district-level escalation would include irrelevant areas' for auto_escalate, and explains the purpose of the address parameter for percentile ranking. It clearly differentiates from other property-related tools by its comparable sales focus.

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 full burden of behavioral disclosure. It effectively explains the dual behavior based on address presence, describes what data is returned in both modes (energy rating, score, floor area, construction age, heating costs for single property; rating distribution, floor area range, property type breakdown for area view), and clarifies the aggregation approach for area analysis.

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 efficiently structured with a clear opening statement, followed by two distinct usage scenarios, and ending with parameter explanations. Every sentence adds value, with no redundant information or unnecessary elaboration.

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 tool with 2 parameters, 0% schema coverage, and no output schema, the description provides excellent coverage of purpose, usage, and parameter semantics. The main gap is the lack of explicit output format details, though the description does list what data fields are returned in both modes.

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 description coverage, the description fully compensates by explaining both parameters' semantics: 'postcode: UK postcode (e.g. "SW1A 1AA")' and 'address: Street address for exact match (omit for area view).' It clarifies that address is optional and explains the behavioral difference when omitted versus provided.

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 retrieves EPC certificate data for UK properties or postcode areas, specifying both single-property and area-level analysis. It distinguishes from siblings by focusing on energy rating data rather than company searches, property transactions, or other real estate functions.

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 provides when-to-use guidance: 'With address: returns the matched certificate for that property' and 'Without address: returns all certificates at the postcode with area-level aggregation. Use this for area analysis rather than a single-property lookup.' This clearly distinguishes between the two usage modes and their appropriate contexts.

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 full burden. It discloses the data sources (Land Registry and Rightmove) and the output (gross yield figure), but lacks details on rate limits, error handling, or authentication needs. It adds some behavioral context but is incomplete for a tool with no 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?

The description is appropriately sized and front-loaded with the core purpose, followed by a structured parameter list. Each sentence earns its place, though the parameter explanations could be slightly more integrated into the flow rather than listed separately.

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 annotations and no output schema, the description is moderately complete. It covers parameters well but lacks details on output format, error cases, or performance characteristics. For a tool with 5 parameters and complex data sources, more behavioral context would improve 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 description coverage is 0%, so the description must compensate. It provides detailed semantics for all 5 parameters, including examples (e.g., 'NG11'), defaults, and explanations of each parameter's role (e.g., 'Sales lookback period in months'), adding significant value beyond the bare 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 specific verb ('calculate') and resource ('rental yield for a UK postcode'), and distinguishes it from siblings by specifying it combines Land Registry sales data with Rightmove rental listings. This is precise and differentiates from tools like 'property_comps' or 'rental_analysis'.

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 calculating rental yield in UK property contexts but does not explicitly state when to use this tool versus alternatives like 'property_comps' or 'rental_analysis'. No exclusions or specific scenarios are provided, leaving usage context inferred rather than guided.

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 full burden and does well by disclosing key behavioral traits: it describes the auto-escalation logic (widens radius if <3 listings), explains what 'thin market' means, specifies the return data structure, and mentions the optional yield calculation. However, it doesn't cover rate limits, authentication needs, or error conditions.

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 efficiently structured with a clear purpose statement first, followed by return values, then behavioral details, and finally a well-organized parameter section. Every sentence adds value with no redundancy or 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?

For a 5-parameter tool with no annotations and no output schema, the description provides excellent coverage of inputs and behavior. The main gap is lack of output format details (structure of returned data) and error handling. Given the complexity, it's nearly complete but missing these final details.

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 description coverage, the description fully compensates by explaining all 5 parameters: postcode format example, radius default and unit, purchase_price purpose for yield calculation, auto_escalate logic, and building_type filter codes. Each parameter gets meaningful context beyond basic schema typing.

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 performs 'rental market analysis for a UK postcode' with specific outputs (median/average rent, listing count, rent range, optional gross yield). It distinguishes from siblings like property_yield or property_comps by focusing specifically on rental market data rather than property transactions or comparisons.

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 context (UK postcode analysis) but doesn't explicitly state when to use this vs alternatives like property_yield or property_comps. It mentions auto-escalation behavior for thin markets, which provides some situational guidance, but lacks explicit 'when-not' or alternative tool recommendations.

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 full burden. It discloses the return data structure (price, tenure, etc.) which is valuable behavioral information, but doesn't mention rate limits, authentication requirements, error conditions, or whether this is a read-only operation. It provides some context but leaves significant behavioral aspects unspecified.

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 efficiently structured with purpose statement, usage guidance, return values, and parameter details in logical sections. While slightly longer than minimal, every sentence adds value. The Args section could be integrated more seamlessly, but overall it's well-organized and front-loaded.

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 single-parameter read operation with no output schema, the description provides good coverage: purpose, alternative guidance, return data structure, and parameter semantics. It doesn't explain the return format (object structure, nested objects) or error handling, but given the tool's relative simplicity and lack of annotations, it's reasonably 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?

With 0% schema description coverage and only one parameter, the description fully compensates by providing clear semantics: it explains what property_id represents (Rightmove property URL or numeric ID) and gives concrete examples of both formats. This adds complete meaning beyond the bare 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 specific action ('Fetch') and resource ('Rightmove listing by ID'), distinguishing it from sibling tools like rightmove_search (which searches) and property_report (which generates reports). It explicitly identifies the target resource type and primary operation.

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 explicit guidance on when to use an alternative ('Prefer the listing://{property_id} resource instead'), creating clear decision criteria between this tool and another approach. This directly addresses the 'when-not-to-use' scenario with a named alternative.

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 full burden. It mentions what data is returned (prices, addresses, etc.) and pagination behavior (~25 listings per page), but lacks critical behavioral details like rate limits, authentication requirements, error conditions, or whether this is a read-only operation. The description doesn't contradict any 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 well-structured and front-loaded: purpose statement first, return values second, then detailed parameter explanations. Every sentence adds value with no redundancy. The parameter section is organized clearly despite covering 10 parameters.

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 10-parameter search tool with no annotations and no output schema, the description does well on parameters but has gaps. It explains what data is returned but not the structure or format. Behavioral aspects like rate limits, authentication, and error handling are missing. The parameter coverage is excellent, but other contextual elements are incomplete.

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 description coverage and 10 parameters, the description provides excellent parameter semantics. It explains each parameter's purpose, format examples (postcode format), valid values (property_type options), building_type codes, default values, and practical context (radius 'default varies by area', max_pages relationship to listings). This fully compensates for the schema 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 the tool's purpose with specific verb ('Search') and resource ('Rightmove property listings'), including scope ('for sale or rent near a postcode'). It distinguishes from siblings like 'rightmove_listing' (likely for individual listings) and other property tools by focusing on search functionality.

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 context through the parameter explanations (e.g., property_type defaults to 'sale'), but doesn't explicitly state when to use this tool versus alternatives like 'property_comps' or 'rightmove_listing'. No guidance on prerequisites or exclusions is provided.

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 full burden of behavioral disclosure. It describes the tool's function and parameter effects (e.g., surcharges, reliefs), but does not cover aspects like rate limits, error handling, or output format. It adds useful context on tax rules but misses broader behavioral traits.

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

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

The description is front-loaded with the core purpose in the first sentence, followed by a structured 'Args:' section that efficiently explains each parameter. Every sentence earns its place by providing essential information without redundancy, making it appropriately sized and well-organized.

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 annotations and no output schema, the description provides good coverage of the tool's purpose and parameters. However, it lacks details on the return value (e.g., tax amount, breakdown), error conditions, or dependencies, leaving gaps in completeness for a calculation tool with multiple inputs.

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 description coverage is 0%, so the description must compensate fully. It provides detailed semantics for all 4 parameters beyond the schema: 'price' is explained as 'Purchase price in £', and each boolean parameter includes clear explanations of their effects (e.g., '+5% surcharge', 'first-time buyer relief', '+2% surcharge'), adding significant value.

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 specific verb ('Calculate') and resource ('UK Stamp Duty Land Tax (SDLT) for a residential property'), making the purpose unambiguous. It distinguishes this tool from all sibling tools, which focus on company searches, property data, or resource management rather than tax calculation.

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 SDLT calculation on residential properties, but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. No sibling tools appear to offer similar tax calculation functions, so the context is clear but lacks explicit guidance on scenarios or prerequisites.

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