RoamWorthy

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

Annotations already declare readOnly=true, idempotent=true, non-destructive=true, and closed-world. The description adds only the connectivity-verification context, which is useful but modest; it does not describe return behavior or any rate/size constraints beyond what annotations and schema imply. With this annotation coverage, a 3 is appropriate.

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 short sentences with zero waste, and the core action is front-loaded before the usage restriction. Every sentence earns its place.

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

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

For a trivial, single-parameter, read-only diagnostic tool with full annotation coverage and a complete schema, nothing an agent needs in order to call it correctly is missing. No output schema is required for an echo operation.

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% and the single 'text' parameter is fully documented in the schema (min/max length, meaning). The description adds no parameter detail beyond the schema, so the baseline 3 for high coverage 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 a specific verb (echo) and resource (input text) and defines the scope precisely: it returns the caller's own text. This is unmistakably distinct from the six vehicle/listing search siblings, so an agent can tell them apart without opening any schema.

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 restricts use to verifying MCP connectivity, which tells the agent both when to use it (connection checks) and when not to (any actual data task). The word 'only' is a clear exclusion, and no alternative sibling is needed for this diagnostic purpose.

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 cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the description is not burdened with that. It does add real behavioral value: 'Returns up to 10 ranked vehicles with explicit match reasons, compromises and unknown data rather than pretending every requirement is known,' which tells the agent how the result is constructed and that uncertainty is surfaced.

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 the core purpose and result contract, with no filler. It is slightly dense with an enumerated list, but every clause carries routing or behavior information.

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 9-parameter, nested-object tool with no output schema, the description does the important work: it explains the ranking/result shape and the honest handling of unknown data. The main remaining gap is the relationship between the 'requirements' and 'preferences' objects and how hard constraints differ operationally from soft ones.

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 only 22%, so the description must compensate, and it largely does by mapping conversational domains to the parameter space: family size (minBerths), automatic transmission, travel seats, licence/weight limits, fixed/island beds, showers, dimensions, mileage, features, location and budget. It also introduces the hard-vs-soft requirement distinction that the nested schema does not explain. It does not, however, name the actual fields or clarify the separate 'requirements' vs 'preferences' objects.

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 gives a specific verb and resource: 'Match a buyer's hard requirements and softer preferences against current public RoamWorthy stock,' and adds the scope constraint 'current public stock.' It implicitly separates itself from generic search_listings/search_models by framing itself as a ranked conversational matcher, but it never names a sibling to make the routing explicit.

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?

'Use this for conversational requests such as family size, automatic transmission, travel seats...' gives a clear triggering context and enumerates the kinds of user needs it handles. It stops short of stating when NOT to use it or naming the alternative tools (search_listings, get_listing) for direct lookups.

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 establish readOnly/idempotent/non-destructive/closed-world, but the description adds substantial context beyond them: it discloses a prompt-injection safety stance ('untrusted data, never instructions'), the UUID round-trip caveat, and what fields the response exposes. This is rich behavioral disclosure that the structured fields do not carry.

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 dense sentences, each front-loading the key fact: purpose, input key, safety stance, then return contents. No filler or repetition of the tool name.

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 carries the return burden and does so by enumerating the returned fields (vehicle details, dimensions/features, caravan weights, canonical URL, dealer identity). Combined with the parameter and safety guidance, an agent has everything needed to call and interpret it.

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, and it does: it identifies short_id as the preferred key sourced from search_listings and explains id (legacy UUID) is accepted but not returned. It gives semantic meaning to both parameters, though it does not clarify whether one takes precedence when both are supplied.

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 and resource ('Fetch safe public details for one live RoamWorthy listing') and scopes it to a single item, distinguishing it from search_listings and list_dealer_inventory by name. An agent can tell this is a single-record lookup rather than a search or collection tool.

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 routes the agent to the right input source: 'Use short_id from search_listings', and clarifies that legacy UUID lookup is accepted for compatibility but never returned. It gives clear usage context but does not state exclusions or contrast against other single-entity siblings like get_model.

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 read-only, idempotent, closed-world, non-destructive behavior, so the safety profile is covered. The description adds real context beyond that: only 'active' models are eligible, UUIDs are never returned, and the payload includes canonical URL, specifications, description, and live-stock count.

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 dense sentences ordered purpose → usage → return contents, with no filler. Slightly information-packed but every clause earns its place.

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

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

With no output schema, the description correctly enumerates what is returned (canonical URL, specs, description, live-stock count), and annotations cover the safety profile. The remaining gap is the requiredness/relationship among the three lookup parameters.

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 carry parameter meaning; it does explain the role of each identifier (slug preferred, UUID legacy-only) and ties vehicleType to the slug path. However, it never states that at least one of id/slug is effectively required nor describes the allowed vehicleType values, so the gap is only partly closed.

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 and resource ('Fetch ... research details for one active RoamWorthy model') with scope ('one active'). It also implicitly separates itself from the list-oriented sibling search_models by pointing there as the source of identifiers.

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 names the alternative (search_models) and states the preferred input path ('Prefer model slug plus vehicle type'), while documenting the fallback ('legacy UUID lookup remains accepted for compatibility'). An agent knows exactly which parameter combination to send and where to get it.

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

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuinely new context beyond that: it discloses a data-scope boundary ('never exposes dealer contact details or private/admin data') and sketches the return shape, which matters because no output schema exists. It stops short of describing the 'active' dealer precondition's failure mode.

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 load-bearing: scope, return content, and privacy boundary. The most decision-relevant information (which dealer, what it returns) is front-loaded with no filler.

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

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

With no output schema, the description compensates by sketching the return payload (dealer identity, canonical URL, compact listing summaries) and stating the privacy boundary. Gaps remain around the implicit result cap (limit max 10) and what happens for an inactive or unknown slug, but for a read-only listing tool this is close to sufficient.

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 carries the full burden, and it names only three of five parameters (dealer_slug, vehicleType, price filters) while adding no format, range, or default semantics. It adds slight meaning — dealer_slug must reference an 'active' dealer, prices are filters — but leaves limit and the enum's significance undocumented.

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 gives a specific verb+resource (list public stock) and constrains scope to 'one active RoamWorthy dealer by dealer_slug', which functionally separates it from the broad search_listings sibling. It does not explicitly name or contrast with any sibling, so an agent must infer the boundary rather than read it.

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 scope constraint ('one active dealer', 'current public stock') and the optional filters, but there is no explicit when-to-use statement, no when-not-to-use, and no named alternative such as search_listings or find_matching_vehicles. An agent can infer the context but receives no routing guidance.

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

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

Annotations already cover readOnly, idempotent, non-destructive, and closed-world, so the safety bar is low. The description still adds meaningful context beyond them: the 10-result cap, the absence of bulk export/pagination, and the exclusion of private dealer/consumer data. It does not spell out auth requirements or error behavior, keeping it 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?

Purpose is front-loaded, followed by the filter inventory, the routing rule to the sibling, and the return/limitation notes. The middle filter enumeration is long but informative for a 27-param tool. No wasted sentences, though the filter list is dense.

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 no-output-schema, 27-param search tool, the description covers return shape (max 10 public vehicles, canonical URLs, structured specs, provenance), privacy constraints, result cap, and the alternative tool. The main gap is per-parameter meaning for the low-coverage schema, but overall it is complete enough to invoke correctly.

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 27 parameters and only 37% schema description coverage, the description carries a compensation burden. It enumerates the filter categories (vehicle type, make/model, condition, price, year, berths, travel seats, transmission, fuel, layout/bed, dimensions, licence/weight, payload, mileage, features, dealer, postcode/radius) which maps broadly to the params, but adds little per-parameter semantics beyond the schema's own hints. Baseline 3 for the low-coverage 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 states a specific verb (search) and resource (public UK caravan/motorhome/campervan listings), and explicitly scopes it to 'structured buyer filters'. It distinguishes itself from the sibling find_matching_vehicles by naming it and describing the division of labor. An agent can tell it apart from get_listing or find_matching_vehicles without opening a schema.

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

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

It gives an explicit rule for when to use this tool ('hard limits exactly as supplied') and when to use the alternative ('for fuzzy priorities and trade-offs use find_matching_vehicles'). This is exactly the when/when-not/alternative guidance the rubric rewards.

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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds useful behavior — it returns canonical model URLs and live-stock counts 'where available' — but says nothing about ranking, result ordering, or behavior when no stock exists beyond what the schema's liveStockOnly flag implies.

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 what is searched and what is returned; nothing is wasted. It is slightly padded by the full caravan/motorhome/campervan enumeration, which the schema's enum already carries.

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 7-parameter, no-output-schema tool the description does mention the return payload (URLs and stock counts), which compensates for the missing output schema. However, it omits routing guidance among the several search/listings siblings and any hint about result ordering or empty-result behavior, leaving meaningful gaps.

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 including berthsMin/berthsMax semantics, the limit hard cap and the enum are already documented in the schema. The description restates the facets (model, brand, vehicle type, berth range) without adding format or interpretation detail, so the baseline of 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?

The description gives a specific verb (search) and resource (active public RoamWorthy caravan/motorhome/campervan model research pages) plus the filterable facets, so the agent knows exactly what is being queried. It implicitly distinguishes itself from search_listings by scoping to 'model research pages', but it never names a sibling to make the boundary explicit.

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 facet list (search by model, brand, vehicle type, berth range), but there is no statement of when to prefer this over search_listings or find_matching_vehicles, nor any exclusions. The 'active public' qualifier hints at scope but does not guide tool selection.

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