Wilma MCP Server
Servidor MCP para Wilma
Un servidor MCP (Model Context Protocol) para Wilma – la plataforma de comunicación escolar finlandesa de Visma. Permite que Claude y otros asistentes de IA compatibles con MCP interactúen con datos escolares como horarios, mensajes y más.
Funcionalidades
Horario – Consulta horarios diarios o semanales con asignaturas, horarios y profesores
Mensajes – Lee mensajes de la bandeja de entrada con estado leído/no leído, visualiza el contenido completo, marca como leídos
Destinatarios – Lista los destinatarios de mensajes disponibles (profesores, personal)
Enviar mensajes – Redacta y envía mensajes a profesores
Related MCP server: Dnevnik.ru MCP Server
Requisitos previos
Python 3.11 o superior
Una cuenta de Wilma (estudiante, tutor o profesor)
La URL de Wilma de tu escuela (p. ej.,
https://yourschool.inschool.fi)
Instalación
# Clone the repository
git clone https://github.com/jessemc98/wilma-mcp.git
cd wilma-mcp
# Create virtual environment
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install the package
pip install -e .Configuración
Crea un archivo .env con tus credenciales de Wilma:
cp .env.example .envEdita .env:
WILMA_BASE_URL=https://yourschool.inschool.fi
WILMA_USERNAME=your_username
WILMA_PASSWORD=your_passwordNota de seguridad: Nunca subas tu archivo
.enval control de versiones.
Uso con OpenClaw
Si usas OpenClaw, este proyecto incluye un SKILL.md que enseña automáticamente a tu agente cómo usar las herramientas MCP de Wilma.
Completa los pasos de Instalación y Configuración anteriores.
Añade el servidor MCP a la configuración de tu Claude Code (
~/.claude.jsono.mcp.jsondel proyecto):
{
"mcpServers": {
"wilma": {
"command": "/path/to/wilma-mcp/venv/bin/python",
"args": ["-m", "wilma_mcp.server"],
"cwd": "/path/to/wilma-mcp"
}
}
}Coloca o enlaza simbólicamente el
SKILL.mden tu directorio de habilidades de OpenClaw para que el agente pueda descubrirlo.
Uso con Claude Desktop
Añade el servidor al archivo de configuración de Claude Desktop:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"wilma": {
"command": "/path/to/wilma-mcp/venv/bin/python",
"args": ["-m", "wilma_mcp.server"],
"cwd": "/path/to/wilma-mcp"
}
}
}Reinicia Claude Desktop después de actualizar la configuración.
Herramientas disponibles
get_schedule
Obtén el horario escolar para una fecha concreta.
Parámetros:
date_str(opcional): Fecha para la que obtener el horario. Por defecto es "today".Admite: "today", "tomorrow", "yesterday"
Nombres de días de la semana: "monday", "tuesday", etc. (inglés o finés)
Formatos de fecha: "2024-03-15", "15.3.2024"
Ejemplo: "¿Cuál es mi horario para el lunes?"
get_week_schedule
Obtén el horario de una semana completa.
Parámetros:
start_date(opcional): Fecha de inicio de la semana. Por defecto es hoy.
Ejemplo: "Muéstrame el horario de la próxima semana"
get_messages
Obtén la lista de mensajes de la bandeja de entrada. Cada mensaje muestra un indicador de leído/no leído (📖 leído, 📬 no leído).
Parámetros:
folder(opcional): Nombre de la carpeta – "inbox", "sent", "archive" o "drafts". Por defecto es "inbox".limit(opcional): Número máximo de mensajes a devolver. Por defecto es 20.
Para "sent" y "drafts", el listado muestra el destinatario ("Para:") en lugar del remitente.
Ejemplo: "Revisa mis mensajes" / "Muestra mis mensajes enviados"
get_message
Lee un mensaje específico con su contenido completo. Nota: visualizar un mensaje lo marca automáticamente como leído en el servidor de Wilma.
Parámetros:
message_id: El ID del mensaje a leer.
Ejemplo: "Lee el mensaje 12345"
set_message_read
Marca explícitamente un mensaje como leído. Útil para marcar mensajes como leídos sin leer su contenido completo. Wilma no permite marcar mensajes como no leídos; es una limitación de la plataforma.
Parámetros:
message_id: El ID del mensaje a marcar como leído.
Ejemplo: "Marca el mensaje 12345 como leído"
get_recipients
Obtén la lista de destinatarios de mensajes disponibles (profesores, personal, tutores).
Parámetros:
query(opcional): Filtro de nombre que no distingue mayúsculas/minúsculas (p. ej., el apellido de un profesor). Útil porque la lista completa de destinatarios de una escuela puede ser larga.
Cada destinatario devuelto tiene una cadena id (p. ej., r_guardian=11876_2893&n_class=33) que puedes pasar directamente a send_message.
Ejemplo: "¿A quién puedo enviar mensajes?" / "Busca el destinatario para el Sr. Smith"
send_message
Envía un nuevo mensaje a cualquier destinatario (profesor, miembro del personal o tutor).
Parámetros:
recipient: A quién enviarlo – ya sea el nombre de una persona (p. ej.,"Galiana Fatima", resuelto automáticamente contra la lista de destinatarios) o un id de destinatario deget_recipients(p. ej.,"r_guardian=11876_2893&n_class=33"). Para dirigirse a varias personas, une sus ids con&.subject: Asunto del mensajebody: Cuerpo/contenido del mensaje
Si un nombre coincide con más de una persona, la herramienta devuelve la lista de coincidencias para que puedas elegir un id específico (no adivinará).
Ejemplo: "Envía un mensaje al Sr. Smith sobre los deberes"
Para responder a un mensaje existente, usa
reply_to_messageen su lugar: resuelve el destinatario automáticamente a partir del mensaje original.
reply_to_message
Responde a un mensaje existente. Esta es la forma preferida de responder, ya que gestiona la resolución del destinatario automáticamente a través del formulario de respuesta de Wilma, sin necesidad de buscar IDs de destinatarios.
Parámetros:
message_id: ID del mensaje al que responder (deget_messages)body: Cuerpo/contenido del mensaje de respuesta
Ejemplo: "Responde al mensaje 12345 diciendo que asistiré"
Conversaciones de ejemplo
Una vez configurado, puedes preguntar a Claude:
"¿Cuál es mi horario de hoy?"
"¿Tengo clases el viernes?"
"Muéstrame mis mensajes no leídos"
"Lee el mensaje de mi profesor"
"¿A qué hora empieza la escuela mañana?"
Notas técnicas
Wilma no tiene una API pública oficial. Este servidor realiza ingeniería inversa de la interfaz web.
La autenticación utiliza cookies de sesión obtenidas mediante el flujo de inicio de sesión.
Los datos del horario se extraen de JavaScript incrustado en la página del horario.
Las listas de mensajes usan endpoints JSON por carpeta (
/messages/listpara la bandeja de entrada,/messages/list/outboxpara enviados,/messages/list/archive,/messages/list/drafts); los mensajes individuales requieren análisis HTML.Seguimiento de leído/no leído: La API JSON de Wilma incluye un campo
Statuspor mensaje – verdadero significa no leído, falso/ausente significa leído. Visualizar un mensaje (solicitud GET) lo marca como leído en el servidor. No hay API para marcar un mensaje como no leído.Envío de mensajes: Wilma no expone destinatarios como elementos
<option>. El selector de destinatarios (/messages/recipients) incrusta cada persona contactable como un.recipient-blockcuyo enlacedata-sourcecodifica un selector de la formar_<type>=<id>(p. ej.,r_guardian,r_personnel,r_ownteachers). Para redactar, el servidor hace GET a/messages/compose?<selector>(que devuelve el formulario con unaformkeynueva y el destinatario ya añadido como una entrada ocultar_<type>), rellena los camposSubjectyBodyText, y hace POST con el botónaddsavebtnde "send". Por eso ahora funcionan los mensajes nuevos, no solo las respuestas.Es posible que el servidor necesite actualizaciones si la interfaz web de Wilma cambia.
Desarrollo
# Install with dev dependencies
pip install -e ".[dev]"
# Run tests
pytestFuncionalidades futuras (planificadas)
Calificaciones y evaluaciones
Registros de ausencia/asistencia
Exámenes próximos
Noticias/anuncios escolares
Listados de cursos
Licencia
Licencia MIT – consulta el archivo LICENSE.
Aviso legal
Este es un proyecto no oficial y no está afiliado ni respaldado por Visma. Úsalo bajo tu propio riesgo. Respeta los términos de servicio y los límites de tasa de Wilma.
Contribuciones
¡Las contribuciones son bienvenidas! No dudes en enviar una Pull Request.
Available Tools
8 toolsget_messageA
Read a specific message with full content.
| Name | Required | Description | Default |
|---|---|---|---|
| message_id | Yes | The ID of the message to read. |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must convey behavioral traits. 'Read' implies a non-destructive operation, and 'full content' indicates the return value. However, it does not clarify whether reading affects read status (despite a sibling 'set_message_read'), nor does it mention error handling or authentication requirements. The description provides basic transparency but lacks depth.
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 one concise sentence, front-loaded with the action and resource, with no superfluous words. It efficiently communicates the tool's 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?
For a simple tool with one parameter and an existing output schema, the description is sufficiently complete. It clarifies the scope ('specific message') and the nature of the result ('full content'), which is adequate for an AI agent to understand when and how to use it.
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 describes the single parameter 'message_id' with full coverage. The description adds no extra meaning beyond the schema, just reiterating 'specific message' which corresponds to the parameter. With 100% schema coverage, the baseline 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 clearly states the tool's purpose: reading a specific message with full content. It uses a specific verb ('read') and resource ('specific message'), and effectively distinguishes from the sibling tool 'get_messages' by emphasizing singularity ('specific') and completeness ('full content').
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 context by saying 'specific message' which contrasts with 'get_messages', but it does not explicitly state when to use this tool over alternatives, nor does it mention any exclusions or prerequisites. The guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_messagesA
Get list of messages from a folder.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of messages to return (default 20) | |
| folder | No | Folder to read from. Options: "inbox", "sent", "archive" | inbox |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. 'Get list' clearly signals a read-only operation, but it does not disclose ordering, pagination behavior, folder validation, or whether full message content is returned. It is adequate but thin.
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, front-loaded sentence with no wasted words. Every word contributes to the core 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?
The tool is simple: two fully described parameters and an output schema exist. The description provides the minimal core behavior, and the schema covers parameter details. It does not mention alternatives, but that gap is already captured in usage guidelines.
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 covers 100% of the parameters. The description's phrase 'from a folder' echoes the schema's folder parameter without adding deeper meaning about limit behavior or folder selection 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 uses a specific verb ('Get') and resource ('list of messages') with a clear scope ('from a folder'). The plural 'list' distinguishes it from the sibling tool 'get_message'.
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 no guidance on when to use this tool versus alternatives like get_message, send_message, or set_message_read. It does not mention exclusions or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_recipientsA
Get list of available message recipients (teachers, staff).
Returns: List of recipients with their IDs and roles.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly indicates a read-only list operation via 'Get list' and discloses the return format ('List of recipients with their IDs and roles'). The qualifier 'available' adds useful scope. It does not mention permissions or rate limits, but for a simple getter this is acceptable.
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 concise sentences, front-loaded with the main purpose and immediately followed by the return format. Every word 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 tool with no parameters and a simple return structure, the description is complete. It explicitly mentions the fields returned (IDs and roles) and qualifies the recipients as 'available'. No significant gaps exist.
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 tool has zero parameters, so the input schema is fully self-explanatory. The description adds no parameter semantics, but none are needed. The baseline for no parameters is 4.
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 function: 'Get list of available message recipients (teachers, staff)'. It uses a specific verb ('Get') and a specific resource ('recipients'), and the scope is clarified with the parenthetical. This distinguishes it from sibling tools like get_messages or send_message.
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 in the context of messaging by referring to 'message recipients', but it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions. Sibling tool names suggest its role among messaging tools, but direct guidance is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_scheduleA
Get the school schedule for a specific date.
| Name | Required | Description | Default |
|---|---|---|---|
| date_str | No | Date to get schedule for. Supports: - "today", "tomorrow", "yesterday" - Weekday names: "monday", "tuesday", etc. - Date formats: "2024-03-15", "15.3.2024", "15.3." | today |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Get' implies a read operation, but it does not disclose behavior for invalid dates, timezone handling, or other edge cases. The description is adequate but lacks deeper behavioral context.
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, front-loaded sentence with no superfluous words. Every word carries meaning.
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 read tool with an output schema and clear schema documentation, the description is nearly complete. It lacks explicit sibling differentiation, but the 'specific date' phrasing sufficiently covers the main use case.
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%, with a detailed description of the single parameter including supported formats and default. The tool description adds no further parameter information, hitting the baseline for high schema coverage.
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 verb 'Get' and the resource 'school schedule' for a 'specific date', which distinguishes it from the sibling tool get_week_schedule. It is concise and 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 phrase 'specific date' implies this is for a single day, implicitly contrasting with get_week_schedule. However, it does not explicitly state when to use this tool over alternatives or mention any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_week_scheduleA
Get the school schedule for a full week.
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | No | Start date of the week. Defaults to today. | today |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only says 'Get the school schedule' without stating that it is read-only, any authentication requirements, or how the week is calculated. This leaves important behavioral context unaddressed.
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 main action and resource. There is no unnecessary information or repetition.
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 has low complexity with one well-documented parameter and an output schema, so the description does not need to explain return values. However, it could be slightly more explicit about the exact definition of 'full week' (e.g., starting day, inclusion of weekends), which keeps it from a perfect score.
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 provides 100% coverage for the single parameter 'start_date' with a clear description. The tool description adds no additional parameter meaning beyond what is in the schema, so the baseline of 3 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's function: 'Get the school schedule for a full week.' It uses a specific verb ('get'), a resource ('school schedule'), and a clear scope ('full week'), which distinguishes it from the sibling tool 'get_schedule' that likely handles a different time range.
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 clear context that this tool is for a full week schedule, implying it is appropriate when the user needs a weekly view. However, it does not explicitly mention alternatives or when not to use this tool, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
reply_to_messageA
Reply to a message. This is the preferred way to reply to messages since it handles recipient resolution automatically via Wilma's reply form, without needing to look up recipient IDs separately.
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | Reply message body/content | |
| message_id | Yes | ID of the message to reply to (from get_messages) |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the automatic recipient resolution behavior but does not disclose side effects, permissions, or whether sending the reply affects read state. For a mutation tool, this lack of detail is a gap.
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 with no waste. The opening phrase clearly states the action, and the second sentence provides meaningful context about the tool's advantage.
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 tool with two params and an output schema, the description is fairly complete. It explains the core behavior and key benefit. It could note potential side effects like marking the original message as read, but overall 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?
Schema description coverage is 100%, so the schema already documents both parameters fully. The description adds no extra parameter semantics beyond the schema, making the baseline 3 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 clearly states 'Reply to a message' with a specific verb and resource. It also distinguishes itself from sibling tools like send_message and get_recipients by emphasizing automatic recipient resolution via Wilma's reply form.
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 this is the 'preferred way to reply' and explains why (automated recipient resolution). It implies when to use this tool over alternatives, though it does not explicitly state when not to use it or name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_messageC
Send a message to a teacher or staff member.
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | Message body/content | |
| subject | Yes | Message subject | |
| reply_to_id | No | Optional message ID if this is a reply | |
| recipient_id | Yes | ID of the recipient (use get_recipients to find IDs) |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It says only 'Send a message' with no information about side effects, permission requirements, delivery guarantees, error behavior, or any constraints. This is a complete lack of behavioral transparency.
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, clear sentence with no filler. It is appropriately concise for a simple tool and effectively front-loaded with the verb. Every word serves a 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 the presence of closely related sibling tools ('reply_to_message', 'get_recipients') and the schema, the description is too sparse to provide a complete picture. It lacks usage context and behavioral details, though the output schema does cover return value expectations, slightly reducing the burden.
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 all parameters. The description adds no additional parameter context beyond the schema, keeping it at the baseline score. It does not clarify how 'reply_to_id' might relate to the sibling 'reply_to_message' tool.
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 uses a specific verb 'Send' with a clear resource 'message' and an audience ('a teacher or staff member'), making the basic purpose apparent. However, it does not explicitly distinguish from the sibling tool 'reply_to_message', which could also be seen as sending a message, so full sibling differentiation is missing.
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 no explicit guidance on when to use this tool versus alternatives like 'reply_to_message'. It only states the action without contextual cues about when this is the appropriate choice, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
set_message_readA
Mark a message as read.
Wilma automatically marks messages as read when viewed. This tool explicitly triggers that by viewing the message. Note: Wilma does not support marking messages as unread.
| Name | Required | Description | Default |
|---|---|---|---|
| message_id | Yes | The ID of the message to mark as read. |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the tool works by viewing the message, which is a mechanism detail. Critically, it states that unread is not supported — a significant behavioral limitation. It doesn't mention potential side effects (e.g., idempotency, permissions), but for a simple mutation this is adequate.
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 extremely concise: two sentences plus a note. Every sentence has purpose — the first states the action, the second explains the mechanism, and the note addresses a key limitation. The structure front-loads the purpose immediately.
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 tool with a single parameter, an output schema, and a clear description, this is complete. It covers the action, the mechanism, and the unread limitation. No additional context is needed for an AI agent to select and invoke this 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?
Schema description coverage is 100%, so the baseline is 3. The description adds no extra parameter details beyond what the schema already provides (message_id). It doesn't explain IDs, formats, or how they relate to the viewing action, but that's unnecessary given the schema.
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 uses a specific verb+resource construction: "Mark a message as read." It clearly distinguishes itself from sibling tools like get_message and get_messages by emphasizing that it explicitly triggers the read state rather than simply retrieving content. The distinction is meaningful because Wilma auto-marks messages as read when viewed.
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 clarifies when to use the tool: to explicitly trigger a read state without needing to read the message content. It also notes that Wilma does not support unread, which is an exclusion. However, it doesn't explicitly name alternatives (e.g., get_message) or explain why you'd choose this over them, so guidance is implied rather than fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
8 tool updates
v0.1.0- First observed
get_message - First observed
get_messages - First observed
get_recipients - First observed
get_schedule - First observed
get_week_schedule - First observed
reply_to_message - First observed
send_message - First observed
set_message_read
TDQS
Scored across 8 tools
Most tools are clearly distinct: schedule vs message tools, single vs list retrieval. However, get_message and set_message_read overlap since viewing a message marks it as read, potentially confusing agents. send_message and reply_to_message are also somewhat related but the reply tool has a clear differentiator.
Tool names follow a consistent verb_noun pattern with clear prefixes: get_ for read operations, set_ for state change, send_ and reply_ for message creation. All names are lowercase with underscores and readable.
8 tools is an appropriate size for a school communication platform covering schedules and messaging. Each tool earns its place, and the count is within the typical 3-15 range without feeling bloated or sparse.
The messaging domain covers core operations: list, get, send, reply, mark read, and recipient lookup. Schedule domain provides get by day and week. Minor gaps exist like message deletion or archiving, but these are not essential for the stated purpose.
Maintenance
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