opplevagent-mcp

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

The description adds significant behavioral context beyond annotations: it creates a pending request only, producer reviews and responds, guest email receives a read-only status link, no payment involved, and non-bookable producers are rejected with a clear message. Annotations (readOnlyHint=false, destructiveHint=false) are consistent with this behavior. No contradiction.

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 well-structured, starting with the core purpose in English and Norwegian, then key behavioral notes, then listing required/optional parameters, and ending with an example. Every sentence provides useful information with minimal redundancy.

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?

The description covers the workflow, constraints, and parameter meanings well, but it does not describe the tool's return value or response structure. Since there is no output schema, the description should ideally mention what the tool returns (e.g., a request ID or status). This omission reduces completeness.

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 100%, but the description adds additional context for several parameters: provider_id must come from discover_gardssalg, slot_at is a request (not a confirmation), guest_email only gets a status link, etc. This adds value beyond the schema descriptions.

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 submits a booking request for a Norwegian gårdssalg producer discovered via discover_gardssalg. It uses specific verbs ('submit a booking REQUEST') and distinguishes from sibling tools (discovery and retrieval tools).

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 explicitly says when to use: after discovering a producer via discover_gardssalg and only for those with active booking status. It explains what the tool does NOT do (never creates a confirmed booking) and includes exclusions (paused/not-onboarded producers). It does not provide an explicit alternative tool, but the context is clear.

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 mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral details: results are verified (Brreg-checked), geo-precision flag, sorted nearest-first with lat/lng, and return fields. No contradictions.

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 reasonably concise and well-structured: purpose, filters, geo-features, return info, examples. The bilingual text adds length but is justified. Could be slightly tighter without losing clarity.

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 no output schema, the description covers return fields (title, category, location, description, booking URL) and geo details. Missing pagination or error handling, but for a 16-parameter search tool it is fairly 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?

Schema coverage is 100% with good descriptions for each parameter. The description adds little beyond summarizing filters and repeating constraints (e.g., radius_km applies only with lat/lng). Baseline 3 is appropriate as the description does not compensate for a coverage gap.

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 the opplevagent.no marketplace, distinguishing it from siblings like get_experience (single item) and list_experience_categories (categories). The verb 'search' and resource are specific, and examples solidify purpose.

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 implies when to use (searching experiences with various filters) but does not explicitly state when not to use or point to specific alternatives like get_experience or list_experience_categories. However, the context is clear enough for inference.

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 read-only, idempotent, non-destructive behavior. The description adds significant behavioral details: near-me search sorts by distance, excludes non-geocoded rows, returns rounded distance_km; and booking status is honest (live vs. dark-launch). 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?

The description is informative and well-structured, starting with the main purpose, then providing examples and details. It is somewhat lengthy but efficient, with no wasted sentences.

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 tool has 8 optional parameters and no output schema, the description covers all necessary aspects: how to filter, how near-me search works, booking status, and examples. It is complete for the tool's complexity.

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 100%, so the schema already documents each parameter. The description adds value by explaining the combination of lat/lng with radius_km and the behavior of booking_live, but does not add much beyond the schema's examples.

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's purpose: searching for Norwegian farm-sale drink producers from opplevagent.no's gårdssalg vertical. It specifies the resource (Brreg-registered drink producers) and distinguishes from sibling tools like book_gardssalg and discover_experiences.

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 of when to use the tool (e.g., 'gårdssalg i Vestland', 'cideri near lat 60.4 / lng 5.3', 'bryggeri med booking') and explains the near-me search feature and filtering by county, municipality, and producer type. However, it does not explicitly state when not to use this tool over siblings.

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 readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds the source (opplevagent.no) and lists returned fields, but does not disclose additional behavioral traits like rate limits or auth needs.

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 front-loaded with purpose and includes bilingual content which may be unnecessary for an AI agent but is not overly verbose. Could be slightly more concise but still effective.

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 no output schema, description provides a detailed list of returned fields (title, description, category, location, etc.) and usage instruction (UUID from discover_experiences). This compensates well for the lack of output schema.

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% with UUID format and description. Description provides an example UUID, reinforcing the schema but adding no new semantic information. Baseline 3 is appropriate.

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?

Description clearly states 'Fetch complete details for a single experience' and enumerates the returned fields, making the purpose specific and unambiguous. It implicitly distinguishes from sibling 'discover_experiences' which lists experiences.

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 mentions obtaining UUID from discover_experiences results, guiding the agent on prerequisite. Clear that this tool is for fetching one experience, not listing or booking, but no explicit when-not statement.

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 and destructiveHint=false. The description adds that it returns counts of verified experiences, which is useful behavioral context beyond the safety profile.

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 concise with two sentences in English and Norwegian, but the bilingual content is slightly redundant. Front-loaded with main purpose.

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 no parameters, no output schema, and adequate annotations, the description provides sufficient information: what it does, when to use, and what it returns (categories with counts).

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 exist, so baseline is 4. No additional parameter meaning needed.

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 counts, specifying the resource (categories on opplevagent.no) and action (list with number of verified experiences). This distinguishes it from siblings like discover_experiences.

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 use before discover_experiences for category filter, with example questions like 'hvilke typer opplevelser finnes i Norge?'. This provides clear when-to-use context and differentiates from similar tools.

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