verwachte_salesSale-planning vooruit: aangekondigde en verwachte sales per merk (van/tot, korting), op basis van merk-aankondigingen en onze eigen sale-waarnemingen.
| Name | Required | Description | Default |
|---|---|---|---|
| merk | No | ||
| markt | No | Markt/land voor prijzen, links en codes (standaard nl). | nl |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds context about the data sources (brand announcements and own sale observations) and indicates output details (period and discount), but does not disclose limitations such as data freshness or uncertainty. This is acceptable given 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?
A single, focused sentence that front-loads the purpose ('Sale-planning vooruit') and includes the key scope and data sources. No wasted words.
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 no output schema, the description hints at what the tool returns: sales per brand with period ('van/tot') and discount ('korting'). It also explains the basis of the forecasts. While it doesn't specify response structure or pagination, this is sufficient for a simple read-only query tool with only two optional parameters.
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 only 50%: 'markt' is well-documented with enum and default, but 'merk' has no schema description. The tool description only repeats 'per merk' without explaining what values are valid, exact match, or required. It does not compensate for the undocumented parameter.
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 forward-looking sale planning tool ('Sale-planning vooruit') that provides announced and expected sales per brand, including period and discount. It is specific about the resource (sales) and the source (brand announcements and own observations), and it implicitly distinguishes itself from the sibling 'actuele_sales' by focusing on expected rather than actual 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 clear context: this tool is for planning ahead and viewing expected/announced sales, which tells an agent when to use it. It does not explicitly name alternatives or state exclusions, but the forward-looking framing is enough to separate it from current-sale tools like 'actuele_sales'.
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.