Alfabot MCP Server

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

With no annotations provided, the description carries the full burden. It clearly states that the tool creates a meeting ('Agenda una reunion'), fixes the duration to 30 minutes, and requires an authenticated MCP request with a specific scope. It does not disclose return behavior or potential side effects like calendar invitations, but the core behavioral traits are adequately covered.

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 two sentences long and front-loads the core action and duration before the auth prerequisite. Every sentence earns its place with no unnecessary filler or repetition of schema boilerplate.

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 6-parameter schema, no output schema, and no annotations, the description provides the essential workflow context: check availability first, book a fixed 30-minute slot, and authenticate with the required scope. It could mention what the response contains or what happens after a successful booking, but it is sufficient for an agent to invoke the tool correctly.

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 schema already documents 83% of parameters, so the baseline is 3. The description adds context that startsAt must be a time returned by check_availability and reinforces the 30-minute duration, but these are largely restatements of schema descriptions. No substantial new parameter-level meaning is added.

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 states a specific verb and resource: it schedules a 30-minute meeting with Alfabot. It also clearly differentiates from siblings check_availability and get_plans because it is the action that actually books the meeting.

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 instructs that the meeting time must come from check_availability, giving the agent a clear prerequisite and workflow. It also notes the required Authorization header and scope. It does not explicitly mention when not to use the tool, but the context is strong enough to route the agent correctly.

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?

No annotations are provided, so the description carries the behavioral burden. It indicates a read-only lookup ('Consulta horarios disponibles') and warns against inventing slots, which implies dynamic data. However, it does not disclose validity windows, timezone behavior, or any constraints on the returned availability.

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 short sentences, with the core purpose front-loaded and the critical usage rule stated immediately after. There is no filler or redundancy; every sentence earns its place.

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 simple one-parameter lookup tool, the description provides the essential context: what to query, the meeting duration, and how to use the result. It does not describe the output format, but given the minimal complexity and the presence of a fully documented schema, this is a minor gap rather than a blocking issue.

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 only parameter, 'days', is fully documented in the schema with a description and valid range, giving 100% schema description coverage. The description adds no extra parameter semantics, so the baseline score of 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?

The description states a specific action, 'Consulta horarios disponibles', with a clear object: available slots for a 30-minute meeting with Alfabot. It distinguishes itself from book_meeting by positioning itself as a prerequisite step, so an agent can clearly tell what this tool does.

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?

It gives explicit usage guidance: use the result before calling book_meeting and do not invent schedules. It does not mention exclusions relative to get_plans, but the core workflow sequencing is clear enough to guide correct invocation.

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?

With no annotations, the description carries the full burden and it supplies a decisive behavioral warning: pricing is under validation, displayPrice is intentionally empty, and the agent must not invent amounts. This is genuinely useful beyond the tool name and schema. It does not cover auth, rate limits, or side effects, but 'consulta' signals a read operation and the disclosed pricing caveat is the main risk.

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 short sentences, the first states primary purpose and the second delivers a critical warning; no filler or redundant restatement of the title. Information is front-loaded enough for an agent to parse quickly.

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 simple read-only catalog lookup with two optional parameters and no output schema, the description covers purpose and the most important output quirk (displayPrice). The schema fills in parameter enums/defaults, and the warning prevents a common hallucination. Missing details are minor (exact response shape, lang effect).

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 schema already describes the `product` parameter and lists enums for both parameters; the description adds no input-parameter meaning. It references 'un producto' but not the `lang` parameter or the omission behavior, so at 50% schema coverage there remains a small gap. The pricing caveat concerns an output field, not parameter semantics.

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 opens with a specific verb and object: 'Consulta los planes disponibles de un producto Alfabot para colegios', clearly identifying the action and the resource. The sibling tools are about meetings/availability, so the plan-catalog scope is distinct. The optional-product behavior in the schema reinforces the scope without contradicting it.

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 the tool is for retrieving available school-product plans but gives no explicit when-to-use/when-not-to-use guidance and never mentions alternative tools. No exclusions or sequencing are provided, so an agent must infer fit from the purpose alone.

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