week_dealsDe actuele weekfolder-deals (supermarkt én online) met oude/nieuwe prijs en korting; alleen voor markt nl/be.
| Name | Required | Description | Default |
|---|---|---|---|
| markt | No | Markt/land voor prijzen, links en codes (standaard nl). | nl |
| winkel | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only and non-destructive behavior. The description adds useful context by specifying the result contents (old/new price and discount) and by narrowing the effective market scope to nl/be. It 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 a single compact sentence with no filler. Every part adds scope, output content, or a usage restriction.
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 deal-list tool, the description covers the core return fields and the key usage restriction. However, there is no output schema, the winkel parameter remains unexplained, and no sibling guidance is provided, making the definition minimally adequate rather than 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?
The description clarifies the markt parameter by stating that the tool only works for nl/be, which is more restrictive than the schema enum. However, the winkel parameter has no schema description and is not mentioned in the description either, leaving a meaningful gap at 50% schema coverage.
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 what the tool provides: current week-folder deals with old/new prices and discounts, restricted to nl/be. It is not a tautology and the resource is specific, but it does not explicitly differentiate from sibling tools such as actuele_sales.
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 an explicit market limitation ('alleen voor markt nl/be'), which helps the agent avoid de/fr/es despite the schema enum. However, it does not state when to prefer this tool over siblings or mention any alternative, so the usage guidance remains mostly implicit.
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.