dm-drogerie-markt
Server Details
Real-time product data, semantic search and more from dm-drogerie markt, Europe's leading drugstore.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.5/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes with no overlap. getProductDetails retrieves detailed technical information (ingredients, nutrition, allergens) for specific product IDs, while searchProducts finds products by query and returns metadata (price, category, attributes). The descriptions explicitly state when to use each tool and what they're not for, preventing confusion.
Both tools follow a consistent verb_noun pattern (getProductDetails, searchProducts) with clear action-object naming. The minor deviation is that one uses 'get' and the other uses 'search', which is appropriate for their distinct functions, so this maintains good readability and predictability.
With only 2 tools, the server feels thin for a retail product domain that typically involves browsing, filtering, and detailed queries. While the tools cover core lookup and search functions, the scope might benefit from additional tools for categories, filtering, or recommendations to provide a more complete experience.
The toolset covers basic search and detailed retrieval, but there are notable gaps for a retail domain. Missing operations include browsing by category, filtering search results, getting product availability or stock, and accessing reviews or recommendations. Agents can work around this by using the existing tools creatively, but the surface is not fully comprehensive.
Available Tools
2 toolsgetProductDetailsGet detailed Product InformationARead-onlyIdempotentInspect
Retrieve detailed product information for dm-drogeriemarkt products.
USE WHEN: ingredients, nutrition facts, allergens, usage instructions, warnings, hazard info, product URLs/images
INPUT: DANs (7 digits, preferred) and/or GTINs (8-14 digits) multiple products can be requested at once min 1 / max 50. Use search tool first if only product name is known.
OUTPUT: TOON format (compact YAML-like). Fields: name, brand, description, ingredients, nutrition, allergens, usage, warnings, URLs, images. found=false for unresolved IDs.
NOT FOR: prices, availability, stock, reviews, recommendations
ERRORS: validation error if >50 or no identifiers
| Name | Required | Description | Default |
|---|---|---|---|
| dans | No | DANs (exactly 7 digits, preferred over GTIN) | |
| gtins | No | GTINs (8-14 digits) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating safe, repeatable operations. The description adds valuable behavioral context beyond annotations: it specifies input validation rules (min 1/max 50 identifiers, validation errors), output format (TOON format), and handling of unresolved IDs (found=false). No contradictions with annotations exist.
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 with clear sections (USE WHEN, INPUT, OUTPUT, NOT FOR, ERRORS) and front-loaded key information. It avoids unnecessary fluff, though the formatting with all-caps section headers could be slightly more polished. Every sentence serves a purpose in guiding tool usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, rich annotations, and lack of output schema, the description provides excellent completeness. It covers purpose, usage guidelines, input constraints, output format, exclusions, and error conditions. The agent has all necessary context to invoke this tool correctly without needing an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (dans and gtins) with their types and digit constraints. The description adds minimal extra semantics: it clarifies that multiple products can be requested (1-50) and that DANs are preferred over GTINs, but doesn't provide significant additional meaning beyond the schema's thorough documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Retrieve detailed product information') and resource ('dm-drogeriemarkt products'), distinguishing it from the sibling searchProducts tool. It provides concrete examples of what information is retrieved (ingredients, nutrition facts, etc.), making the purpose 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?
The description explicitly includes 'USE WHEN' and 'NOT FOR' sections that specify when to use this tool (for detailed product info like ingredients, allergens) versus when not to use it (for prices, availability, reviews). It also references the alternative 'search tool' when only product names are known, providing clear guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchProductssearchProductsARead-onlyIdempotentInspect
Search for products available in the German dm-drogerie market (online and local stores).
USE WHEN: searching dm-drogerie products by name, category, ingredient, property, or any
natural language query (any language supported). Often answers questions about
ingredients and properties directly. Covers: dm-drogerie markt brands, make-up,
skincare, perfume, hair, health, nutrition, baby & child, household, home & living,
photo, and pets.
OUTPUT: GTIN, DAN, brand, title, details, category, price, appLink (direct
product URL), description, highlights/USPs, and extensive attributes including:
- Dietary/Allergen: vegan, vegetarian, bio, glutenFree, lactoseFree, sugarFree,
nutFree, soyFree
- Cosmetic Ingredients: fragranceFree, alcoholFree, parabenFree, sulfateFree,
preservativeFree, dyeFree, oilFree, siliconeFree, naturalCosmetics
- Product Properties: waterproof, new, limitedEdition, sellout, onlineOnly,
exclusiveDm, dmBrand, purchasable
NOT FOR: nutritional information (calories, protein, carbs, fats), complete allergen
lists, full ingredient details. For these, use 'getProductDetails' tool with
the GTINs or DANs.
LIMITATIONS: Only make claims based on EXPLICITLY stated product highlights/descriptions.
Do NOT extrapolate or assume properties not mentioned in the results.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The search query for dm-drogerie products |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating safe read operations. The description adds valuable behavioral context about language support, coverage of product categories, and the important limitation about not extrapolating from results, which goes beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections (purpose, USE WHEN, OUTPUT, NOT FOR, LIMITATIONS). Every sentence adds value - no redundant information. The description is appropriately sized for the tool's complexity.
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 good annotations and a simple single-parameter schema, the description provides excellent context. It clearly explains what the tool does, when to use it, what it returns, what it doesn't do (with alternative), and important limitations - all without needing an output schema.
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 100% schema description coverage, the input schema already documents the single 'query' parameter. The description adds some context about what can be searched (name, category, ingredient, property, natural language) but doesn't provide additional syntax or format details beyond what the schema implies.
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 products in the German dm-drogerie market, specifying both online and local stores. It distinguishes from its sibling 'getProductDetails' by explaining this tool is for search while the sibling provides detailed nutritional/allergen information.
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 includes explicit 'USE WHEN' guidance for searching by various criteria and 'NOT FOR' exclusions with a named alternative tool ('getProductDetails'). It also provides 'LIMITATIONS' about making claims only based on explicitly stated information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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