Get the booking link to schedule a free 30-minute call with Laurent Knauss (Cal.com). The agent should present this link to the user so they can pick a slot. Optional topic hint is allowed but the actual slot selection happens on Cal.com.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | No | Optional topic for the call (e.g. 'agentic AI project'). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It clearly states that the tool only retrieves a booking link and that actual slot selection happens externally on Cal.com, preventing the agent from promising booking functionality. It doesn't mention return format or edge cases, but the key behavioral boundary is well communicated.
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 focused sentences with no filler. The core purpose is front-loaded and the important behavioral caveat about external slot selection is included without unnecessary detail.
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 tool is simple: one optional parameter, no output schema, no annotations. The description tells the agent what to do with the result (present the link) and what not to do (select the slot). This is sufficient for a correct invocation.
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% and the topic parameter is already documented as optional. The description adds value by clarifying that topic is only a hint and cannot be used to select the slot, which goes beyond the schema's basic explanation.
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?
States the specific verb and resource: getting a booking link to schedule a free 30-minute call with Laurent Knauss via Cal.com. The description also clearly differentiates this from the sibling content-retrieval tools (get_article, get_profile, etc.) by making the booking purpose explicit.
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?
Clearly implies use when a user wants to schedule a call with Laurent Knauss, and clarifies the agent's role is to present the link rather than handle booking. It doesn't explicitly list alternatives or exclusions, but sibling names are obviously unrelated, so the intended use case is clear enough.
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 maps to a distinct resource and action: booking a call, viewing one article, viewing the profile, viewing skills, and listing articles. While get_profile includes a Cal.com link, book_call is clearly the purpose-specific tool for scheduling, so there is no real ambiguity.
All tool names follow a consistent lower_snake_case verb_noun pattern: book_call, get_article, get_profile, get_skill, list_articles. Singular get_* tools and the plural list_articles follow an intuitive, predictable convention.
Five tools is well-scoped for a personal website/portfolio server. Each tool covers a meaningful surface area without redundant or filler operations.
The toolset covers the core visitor and agent needs: discovering and reading article metadata, retrieving the profile and contact details, assessing skills, and booking a call. Article content is intentionally available via the returned canonical URL, so there are no dead ends.
