XFish Horgász Webáruház

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

No annotations provided, so description carries full burden. It adds valuable context about return structure (category tree with ID, név, szülő, termékszám), but lacks disclosure on read-only nature (implied but not explicit), pagination, rate limits, or error behaviors.

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

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

Two well-structured sentences with zero waste. First sentence establishes operation and domain; second sentence details return value composition. Front-loaded with essential 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 2-parameter read operation with no output schema, the description adequately compensates by documenting return fields. Missing explicit read-only declaration given lack of annotations, but sufficient for tool selection and basic invocation.

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 has 100% description coverage with detailed field documentation (including enum mapping for webshop_id and parent_id logic). Description does not duplicate parameter info, which is acceptable given complete schema coverage. Baseline 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 uses specific verb 'listázása' (listing) with resource 'kategóriák' (categories) from 'XFish.hu webáruház', clearly distinguishing from product-focused siblings (get_product_details, search_products). It also specifies return data structure (category tree with ID, name, parent, product count).

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 explicit when-to-use or when-not-to-use guidance provided. While the distinction between categories and products is clear from the description, there is no explicit guidance on choosing this over siblings or prerequisites for use.

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 provided, so description carries full burden. Mentions it lists manufacturers but lacks details like pagination, ordering, limited results, or read-only nature. Adequate but could be more transparent.

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 concise sentences with no redundancy. Every sentence adds value: first states purpose, second explains the use of output for another tool.

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

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

No output schema, so description should cover return structure. It states returns manufacturer IDs but not format (e.g., list of objects). Lacks pagination or size limits. Mostly complete for a simple list 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 coverage is 100% with descriptions for both parameters. Description adds valuable context by linking output to search_products, beyond schema. No extra parameter details beyond schema, but sufficient.

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?

Clear verb (list) and resource (manufacturers/brands) with explicit purpose: returns IDs needed for search_products. Distinguishes from sibling tools like get_categories by linking to its output usage.

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 that output (manufacturer IDs) are used for search_products manufacturer_id parameter, providing context. No explicit when-not-to-use, but clarity on integration with sibling tool.

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 must carry the full burden. It adds valuable behavioral context by disclosing exactly which fields are returned (name, price, stock, etc.), effectively substituting for a missing output schema. However, it lacks disclosure of error handling (what happens if product_id doesn't exist), authentication requirements, or explicit confirmation that this is a safe read-only operation.

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, efficiently structured sentence that front-loads the action (retrieval) and follows with the specific data fields returned. There is no redundant or wasteful text; every element serves to clarify the tool's purpose or output.

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 lookup tool with one parameter and no output schema, the description is reasonably complete. It compensates for the missing output schema by enumerating the returned fields. However, it could be improved by mentioning error cases (e.g., product not found) or confirming the read-only nature of the 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?

The input schema has 100% description coverage (product_id is documented as "Termék ID"). Since the schema fully documents the single required parameter, the baseline score is 3. The description does not add additional parameter semantics (e.g., format constraints, examples), but none are needed given the complete 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 it retrieves detailed data of a specific product ("Egy adott termék részletes adatainak lekérdezése") and explicitly lists the returned fields (name, price, description, stock, image, manufacturer, article number). This distinguishes it from sibling tools: get_categories (returns categories) and search_products (returns search results, not detailed single-product data by ID).

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 phrase "adott termék" (specific/given product) implies usage when a specific product ID is already known, contrasting implicitly with search_products. However, there is no explicit guidance on when to use this versus search_products, nor any mention of prerequisites or error conditions (e.g., invalid product_id).

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 and successfully notes the bilingual search capability ('Magyar és angol nyelvű keresés is működik') and specific domain (XFish.hu). However, it omits operational details such as pagination behavior, result format, or error handling that would fully characterize the tool's runtime 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 consists of three efficient sentences that front-load the tool identity, enumerate search dimensions, and specify language support without redundant phrasing. Every sentence contributes distinct information about the tool's function, scope, or behavioral traits.

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 rich schema with 100% coverage, the description adequately covers the tool's purpose and domain context, though it cannot fully compensate for the missing output schema regarding return structure. The description appropriately focuses on search semantics but leaves gaps around result pagination and explicit sibling relationships.

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 input schema has 100% description coverage, establishing a baseline where parameter semantics are already clear; the description adds conceptual grouping of parameters (mapping 'szöveg' to query, etc.) and the bilingual note for query terms. Since the schema already documents all parameters thoroughly, the description's additional value is limited to high-level categorization.

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 identifies the tool as a product searcher ('Termékkereső') for the XFish.hu fishing webshop ('horgász webáruház'), specifying the exact domain and resource type. It distinguishes the general search functionality from likely retrieval-focused siblings by emphasizing the filtering capabilities (text, category, manufacturer, price).

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?

While the description lists available search filters (text, category, manufacturer, price), it provides no explicit guidance on when to use this broad search versus the get_product_details tool for specific lookups. The lack of when-not guidance or explicit comparison to siblings leaves usage context implied rather than stated.

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