Loppix catalog and configuration

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

All annotations are false, conveying no safety profile, so the description carries the full burden. It adds genuinely useful disclosure: the tool has no financial side effects (no purchase, no reservation, no cart, no billing approval) and produces a short-lived link. This goes beyond the annotations meaningfully. 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?

The description is brief and front-loaded, leading with the core purpose and then a compact list of exclusions. It is efficient with no wasted sentences. Minor note: it is written in Croatian, which is a localization consideration rather than a structure flaw.

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 12 parameters, no output schema, a nested crop object, and all-false annotations, the description should carry substantial weight. It covers the behavioral safety well but omits all parameter semantics, does not describe the return value or link lifetime, and does not clarify which of the many fields are needed to produce a valid handoff. This is inadequate for a tool of this 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 description coverage is 0% and there are 12 parameters including a complex nested 'crop' object. The description provides zero information about motifId, crop, designType, materialId, widthCm, heightCm, or any other parameter. The description completely fails to compensate for the very low schema coverage, leaving an agent to guess at how to construct valid input.

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 and resource ('issue a short-lived link for viewing the complete configuration') and explicitly enumerates what it is NOT (purchase, reservation, cart, payment approval). This clearly distinguishes it from quote_configuration and validate_configuration siblings, so an agent can tell what this tool does and doesn't do without opening the 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?

The 'does not' list (no purchase, no reservation, no cart, no payment approval) gives clear exclusions and the 'customer reviews and confirms on Loppix' phrase conveys when it's appropriate — handing off for external confirmation. However, it never names the alternative tools (quote_configuration, validate_configuration) that an agent should reach for instead, so guidance on when NOT to use it is implied rather than explicit.

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?

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safe read nature is covered. The description adds useful context by saying the record is public and by listing the fields returned, though it does not disclose failure/not-found behavior or auth requirements.

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 two short sentences: the first front-loads the operation and the second summarizes the return fields. There is no filler, and each sentence contributes useful 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 low-complexity, safe, idempotent read operation with a single required parameter, the description covers the core behavior and even provides return-field context that would otherwise be missing since there is no output schema. It lacks detail about not-found/error behavior, but the overall profile is 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?

Schema description coverage is 0%, and the description only restates 'by ID' without giving any meaningful detail about what the ID represents, where it comes from, or how to obtain it. The schema gives only min/max length, so the description adds little beyond restating the parameter name.

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 a specific verb and resource ('Dohvati javni zapis znanja prema ID-u') and even lists the expected return values (source, revision, freshness, unknowns). It is clear enough to recognize a single-record fetch-by-ID operation, but it does not explicitly contrast itself with sibling tools such as search_knowledge.

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

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

Usage is only implied: call it when you have an ID for a public knowledge record. The description gives no explicit 'when to use vs. alternatives' guidance and does not mention that search_knowledge should be used when the ID is unknown, so some inference is left to the agent.

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?

The annotations already cover readOnly, idempotent, and non-destructive behavior, but the description adds a useful semantic boundary: the result includes known limitations and the tool should not be treated as evidence of undocumented safety or starting prices. That goes beyond the structured hints, though it does not describe return format or pagination.

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 one compact sentence, front-loaded with the operative purpose and followed by a boundary condition. There is no padding, and every clause carries enough information to keep the definition useful.

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

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

For a simple read-only tool with one optional enum parameter, the definition is close to sufficient, and the annotations handle the safety profile. However, it leaves parameter semantics and when-to-use-versus-siblings unexplained, and it does not fill the total absence of output-schema guidance.

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% and the description never mentions productType, its default, or how choosing wallpaper/canvas affects results. The enum in the schema gives value candidates, but the description contributes no meaning beyond that, so the agent is left to infer the relationship between productType and materials.

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 opening clause states a clear verb and object: 'get materials and known limitations', which distinguishes it from sibling tools like get_knowledge and get_motif by resource type. It does not explicitly explain the productType dimension, and the disclaimer about undocumented safety/starting prices is more of a constraint than a purpose statement.

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?

There is no guidance about when to choose get_materials over search_motifs, get_motif, or the other siblings, nor any mention of prerequisites. The intended use is only implied by the resource name, which is not enough for an agent deciding between 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?

The description discloses the specific data payload (versions, images, canonical URL, revision, decisions), which adds value beyond the annotations that already indicate read-only, idempotent, and non-destructive behavior. It does not contradict the annotations and provides useful context about the return content.

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, focused sentence that lists the key return elements without fluff. It is efficiently structured and front-loads the core purpose, with no unnecessary repetition or digressions.

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?

The description lists the data types returned, providing a basic understanding, but does not specify the response structure, error conditions, or any dependencies. Given the lack of an output schema, a more detailed description of the return format would be beneficial, though it remains adequate for a simple get 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?

With 0% schema description coverage, the description should explain the motifId parameter. It only indirectly references 'one motif', leaving the parameter's format, meaning, and constraints undefined. The agent must rely on the parameter name alone, which is minimal compensation.

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 action (get) and the resource (one motif), enumerating specific data returned: public versions, images, canonical URL, revision, and required decisions. This distinguishes it from sibling search_motifs, which implies searching rather than retrieving details for a specific motif.

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?

No guidance is provided on when to use this tool versus alternatives such as get_knowledge or search_motifs. The description only states what it does without indicating preferred contexts or exclusions, leaving the agent to infer appropriate usage.

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 this as read-only, non-destructive, and idempotent. The description adds useful behavioral nuance: the result is in EUR cents, pricing follows Medusa, missing configuration fields mean the configuration is not ready, and delivery/final total are deferred to checkout. This does not contradict the 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 three short sentences with the core purpose front-loaded firstharexpected. The second sentence gives usage constraints and the third clarifies final pricing scope. There is no filler or 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?

The core behavior, pricing unit, and checkout caveat are present, which is helpful. However, there is no output schema, and the description does not explain the response shape or fully cover the large parameter surface, so an agent may still be unsure what to expect or how to handle the many optional/conditional 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?

With 0% schema description coverage, the description carries the burden for explaining parameters, but it only mentions 'dimensions and material' at a high level. It leaves the many other parameters (crop, colorwayId, designType, repeatScale, catalogRevision, pricingRevision, quantity) unexplained and does not help the agent understand how to supply them 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 clearly states the tool computes a product quote in EUR cents using Medusa pricing rules, giving a specific verb, resource, and unit. It does not explicitly differentiate from the sibling validate_configuration, but the calculate-versus-validate and quote-versus-handoff functions are implicit in the wording.

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 should be called when dimensions and material are availableading and that a missing field makes the configuration unfinished)Skip. It does not explicitly mention when to prefer validate_configuration or create_configuration_handoff, leaving sibling selection mostly to the agent's inference.

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 read-only, idempotent, and non-destructive behavior, so the description adds the freshness indicator and the limitation to source-based answers, which is useful context beyond annotations. However, it doesn't detail pagination or how freshness is represented.

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 short, with the key functional point front-loaded. Every sentence adds value—first describes the main output, second sets a boundary, third specifies a fallback for unknown data. No waste.

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 read-only search tool, the description covers core behavior and an important limitation, but lacks detail on return structure (e.g., how freshness is presented) and explicitly names alternatives. Given the complexity is low and no output schema exists, it's adequate but not fully 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 0%, so the description provides no parameter details, but parameters (query, limit, offset) are standard and self-explanatory. The description doesn't clarify the query syntax or how freshness relates to limit/offset, but the schema defaults and limits are clear, so baseline 3 is appropriate.

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

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

The description clearly states the tool searches for answers with sources and freshness indicators, and explicitly notes it does not provide answers outside sources. It differentiates from sibling tools like get_knowledge, which likely retrieves specific knowledge entries, by focusing on search with fresh markers, though it doesn't name 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 implies usage for finding sourced answers but does not explicitly state when to use this tool versus get_knowledge or other siblings. It mentions checking INMAR for unknown technical data, which hints at limits, but lacks clear when-to-use or when-not-to-use 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 mark the operation readOnly, idempotent, and non-destructive, so the safety profile is covered. The description adds behavioral context beyond that: returned images are 'inspirativni prikazi, ne dokaz izvedbe' (not proof of execution) and 'Bez cijene prije konfiguracije' (no price before configuration), which manages expectations about results.

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 short sentences front-load the purpose and then add two high-value caveats. No redundant phrasing or restatement 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?

For a read-only search tool, the description plus annotations cover the core action, key filters, and two important behavioral caveats (image reliability and pricing). It omits explicit mention of the kind filter and pagination behavior, but those are visible in the schema with sensible defaults, so the gap is minor.

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 the semantic load. It maps 'naziv' and 'atmosfera' to the query concept, and explicitly names 'kategorija' and 'prostorija' matching the category and room fields, but it does not mention kind, limit, or offset. The uncovered parameters are reasonably self-explanatory from the schema, so the description partially compensates.

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 opens with the verb 'Pretraži' (search) and the resource 'originalne motive', and lists the searchable dimensions (name, atmosphere, category, room). This makes it immediately distinguishable from sibling tools like get_motif (single retrieval) and search_knowledge (knowledge articles).

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 is for finding motifs by free-text/atmosphere and filters, but it never states when to prefer it over get_motif or search_knowledge, nor any exclusion criteria. An agent can infer usage from the verb but receives no explicit 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds some business-relevant context by saying it does not create a cart, order, or email, which is closer to the user-facing meaning of the safe read-only behavior. However, it does not explain what the validation returns, whether validation failures are thrown, or how results are reported; with annotations already carrying the main safety profile, this is adequate but not rich.

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 two short, front-loaded sentences with no fluff: it states what is checked and what is not created. It is concise, though given the complexity of the tool, the brevity could have been organized into parameter categories while still being concise.

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 12-parameter tool with a nested crop object, no output schema, and all 28 descriptors blank in the schema, this description is too bare to let an agent confidently invoke the tool correctly. Missing elements include required fields, validation semantics, rejection behavior, and what a successful result looks like. The negative side-effect statement is useful but does not fill the other 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 0%, so the description carries the burden of explaining 12 parameters and a nested crop object. The description only hints at dimensions, material, design type, and repeat, but never names or explains required inputs such as motifId, crop, colorwayId, designType, or revision fields. This is insufficient compensation for an entirely 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 says the tool checks whole centimeters, material, execution, and repeat/pattern, and it states it does not create a cart, order, or email. This is a specific validation action with a clear scope, and the negatives help distinguish it from transactional tools. It does not explicitly name sibling tools, but the core purpose is unambiguous.

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?

There is no explicit guidance about when to call this tool versus alternatives like quote_configuration. The name and description imply validation-before-order, but the description does not state prerequisites, other sibling tools, or exclusions. The only usage signal is the negative statement about not creating cart/order/email, which is more about behavior than routing.

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