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lokal_search

Find local food producers in Norway using natural language queries in Norwegian or English. Get ranked results with contact information and vCard links to add producers to your contacts.

Instructions

Search for local food producers in Norway using natural language. Supports Norwegian and English. Returns ranked producers with contact info and a vCard link so the user can add them to their contacts. Examples: 'fresh vegetables near Grünerløkka', 'organic honey Oslo', 'ost Trondheim'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query (Norwegian or English)
limitNoMax results
Behavior3/5

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. It effectively describes key behaviors: natural language processing, bilingual support (Norwegian/English), ranked results, and vCard functionality. However, it doesn't mention important operational aspects like rate limits, authentication requirements, error conditions, or pagination behavior beyond the 'limit' parameter.

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

Conciseness5/5

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

The description is perfectly concise and well-structured: the first sentence establishes core functionality, the second adds important behavioral details, and the third provides concrete examples. Every sentence earns its place with no wasted words, and key information is front-loaded appropriately.

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

Completeness3/5

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

For a search tool with 2 parameters, 100% schema coverage, but no annotations or output schema, the description provides adequate context about what the tool does and how to use it. However, it lacks details about the return format (beyond mentioning vCard links), error handling, or performance characteristics that would be helpful given the absence of structured output documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the schema already documents both parameters thoroughly. The description adds minimal value beyond the schema - it mentions natural language queries in Norwegian/English (implied by the schema's description) and provides query examples, but doesn't explain parameter interactions or provide additional semantic context. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('search for local food producers') and resources ('in Norway'), distinguishing it from siblings by focusing on natural language search rather than discovery, info, or stats. It explicitly mentions the target domain (food producers) and geographic scope (Norway).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool (searching for food producers with natural language queries in Norwegian or English) and includes helpful examples. However, it doesn't explicitly state when NOT to use it or mention alternatives among the sibling tools (lokal_discover, lokal_info, lokal_stats), leaving some ambiguity about tool selection.

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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