product_oordeelOnafhankelijk kwaliteitsoordeel over één product: SupplementScore met onderbouwing, reviews en actuele prijs.
| Name | Required | Description | Default |
|---|---|---|---|
| markt | No | Markt/land voor prijzen, links en codes (standaard nl). | nl |
| product_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds useful context about what the tool returns (SupplementScore, substantiation, reviews, current price) but does not disclose data freshness, limitations, or pricing behavior beyond 'actuele prijs'.
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, front-loaded sentence with no filler. Every element contributes meaning: independence, single-product scope, and the key output components.
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 read-only annotations, simple input schema, and absence of an output schema, the description adequately conveys the tool's return content. It is missing some guidance on alternatives and product_id semantics, but the core information needed to invoke and interpret the tool is present.
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 documents markt with its enum and default but product_id has no description. The description's 'over één product' clarifies that product_id targets a single product, adding some meaning, but it does not compensate fully for the undocumented product_id or explain how markt affects output.
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 provides an independent quality judgment for one product, including SupplementScore, substantiation, reviews, and current price. It is specific about scope and output, though it does not explicitly differentiate from siblings like beste_in_categorie or prijs_historie.
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 gives no guidance on when to use this tool versus alternatives such as beste_in_categorie or score_methodologie. The phrase 'over één product' implies single-product use, but there are no explicit conditions, exclusions, or references to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct concerns: current sales, expected sales, weekly deals, price history, product reviews, discount codes, and search are clearly separable. The main risk is that actuele_sales, verwachte_sales, and week_deals all deal with 'sales/deals', but their temporal and channel scopes are explicit enough to prevent serious misselection.
All tool names use lowercase snake_case and are Dutch descriptive phrases, which gives a coherent feel. The pattern is not strictly verb_noun because most names are noun phrases like product_oordeel and prijs_historie, with zoek_producten as the only verb-led exception, so the set is consistent but not perfectly uniform.
Nine tools is well within the ideal range for a supplement deals/reviews domain. Each tool covers a distinct information need without obvious redundancy or bloat.
The set covers the full user journey for supplement research: searching products, checking current deals, anticipating future sales, validating discounts with price history, retrieving discount codes, reading quality scores, and understanding the scoring methodology. No significant operational gap is apparent for the stated domain.