opplevagent-mcp

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds valuable behavioral details: only verified providers (Brreg-checked), geo-precision flag for near-me searches, distance rounding, and default sorting. No contradictions; the description enhances transparency beyond 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 slightly long but well-structured: main purpose first, then filter list, then near-me specifics, return fields, examples. Every sentence serves a purpose, and front-loading key information helps agents quickly grasp the tool's scope. Minor redundancy (Norwegian/English filter names) is acceptable for completeness.

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 16 parameters and no output schema, the description covers filters, near-me search, return fields, and provider verification. It includes examples and default limit. Missing details like pagination or default sort order (beyond near-me) are minor; overall, agents have sufficient context to use the tool effectively.

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 coverage is 100% for all 16 parameters. The description adds meaning by grouping filters (e.g., fylke, kategori, vær, sesong) and explaining near-me search behavior (lat/lng, radius_km, geo_precision). This goes beyond the schema's individual parameter descriptions, significantly aiding an AI agent in understanding parameter interplay.

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 explicitly states 'Search the opplevagent.no curated marketplace of Norwegian experiences and activities,' providing a specific verb (search) and resource. It distinguishes from siblings: get_experience (single experience) and list_experience_categories (categories only), making the tool's purpose unmistakable.

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 concrete examples and indicates broad search capabilities (natural language, filters, near-me). While it doesn't explicitly state when not to use or compare to siblings, the examples and context imply appropriate scenarios, earning a high score with minor room for explicit exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Description adds behavioral details beyond annotations: near-me search excludes ungeocoded rows, distance is rounded and never fabricated, booking status is honest (live vs. coming soon). No contradiction with 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?

Description is relatively long but well-structured: English explanation, Norwegian summary, then examples. Each sentence adds value, though slight verbosity prevents a 5.

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?

No output schema, but description lists return fields (name, location, producer type, booking status) and explains near-me behavior. Covers all key aspects for a search tool.

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 coverage is 100%, so parameters are well-documented. The description adds context: lat/lng required together, radius_km only with lat/lng, booking_live filter effect. Examples enhance understanding.

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 it searches for Norwegian farm-sale drink producers on opplevagent.no, specifying the data source (Brreg-registered) and filtering capabilities. It distinguishes from sibling tools (discover_experiences, etc.) by focusing on drink producers.

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 provides examples and explains when to use near-me search, filters, and booking status. It doesn't explicitly state when not to use it or mention alternatives, but the context is clear given sibling tools are unrelated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds detail about the rich return fields (title, description, category, etc.), which is consistent. No contradictions, but doesn't mention potential network delays.

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?

Two sentences plus a bilingual intro. Front-loaded with main action. The Norwegian duplicate adds slight redundancy but overall concise and clear.

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 one parameter, no output schema, and annotations covering safety, the description fully covers what the tool does, what it returns, how to obtain the UUID, and provides an example. No gaps.

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 coverage 100% for the single 'id' parameter. The description adds context with an example UUID and ties it to discover_experiences, enhancing understanding beyond the schema's format description.

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 it fetches complete details for a single experience by UUID. It distinguishes from sibling tools (discover_experiences, list_experience_categories) by focusing on a single item, not discovery or categories.

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?

Explicitly tells when to use: 'Obtain the UUID from discover_experiences results.' This directly connects to the sibling tool and provides clear guidance on prerequisite data.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnly and idempotent. Description adds that it returns categories with counts, providing minor behavioral detail beyond 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?

Description includes both English and Norwegian text, which is somewhat redundant. However, it is brief and front-loaded with the main action in the first sentence.

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 parameterless list operation with no output schema, the description adequately explains return content (categories with counts) and usage context. Minor missing details like sorting or pagination are acceptable.

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?

No parameters; schema coverage is 100% and description does not need to add parameter semantics. Baseline score of 4 applies.

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 lists all experience categories with verified experience counts, distinguishing it from siblings by advising usage before calling discover_experiences with a filter.

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?

Explicitly advises using this tool to understand available categories before filtering with discover_experiences. Includes example questions. Lacks explicit when-not-to-use, but sibling context makes it sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.