list_clinic_servicesList the bookable services of one clinic, with duration, price (SEK) and a FHIR HealthcareService per bookable variant. The variant id is what get_available_slots takes.
| Name | Required | Description | Default |
|---|---|---|---|
| clinic_slug | Yes | The clinic slug from search_clinics (the URL segment, e.g. "mickes-klinik-lund"). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it as read-only. The description adds transparency by detailing the output fields (duration, price, HealthcareService, variant id). No behavioral 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 a single concise sentence that front-loads the core action and key output details. Every word serves a purpose with no filler.
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 adequately explains the return type (duration, price, HealthcareService, variant id) and connects to sibling tools. It lacks details like ordering or pagination, but for a simple list tool it is sufficient.
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 sole parameter clinic_slug is well-described in the input schema itself (explaining it's the URL segment from search_clinics). The description does not add additional meaning beyond what the schema provides, so baseline score 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 bookable services for a clinic, including duration, price, and variant id. It distinguishes itself from siblings by mentioning the variant id is used by get_available_slots, making the purpose unambiguous.
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 usage for listing services before calling get_available_slots, but no explicit when-to-use or when-not-to-use guidance is given. It somewhat relies on sibling context for differentiation.
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.
Each tool has a clearly distinct purpose: searching clinics, listing services, getting available slots, and finding the next available date. No overlap in functionality.
All tool names follow a consistent verb_noun pattern (e.g., search_clinics, list_clinic_services, get_available_slots). No mixing of conventions.
With 4 tools, the server is well-scoped for clinic discovery and appointment slot checking. No unnecessary clutter or missing essentials.
The tool set fully covers the discovery workflow: find clinics, see their services, check availability, and handle empty slots with next available date. The server explicitly excludes booking, so no gap.