Evaluates a job offer against the master profile and preferences (work mode, minimum salary by contract type, technologies, English level) and returns fit status with reasons.
Compara la oferta con el perfil maestro y sus preferencias (modalidad, salario mínimo según tipo de contrato, tecnologías declaradas y nivel de inglés) y devuelve encaja, encaja_parcial o no_encaja con los motivos.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations were provided, the description carries the full behavioral burden. It successfully discloses critical operational behavior: the output is not just a boolean but a structured categorical rating (encaja, encaja_parcial, no_encaja) alongside explanatory reasons, which is vital for agent decision-making.
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, dense sentence that packs all necessary information—input function, comparison scope, and output format—without any wasted words. It is highly efficient.
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 that there are no structured annotations or output schemas, the description is remarkably complete. It defines the complex business logic, the data points used for the evaluation, and the precise possible return values, making it fully sufficient for a cognitive agent.
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 0%, so the description must compensate entirely. The tool requires only one parameter, 'id,' but the description fails to clarify whether this 'id' refers to the job offer being evaluated or the master profile against which the offer is being tested.
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 purpose is perfectly clear: it compares an job offer against a master profile. It specifies the comparison criteria (modality, salary, tech, English) and the three possible qualitative outcomes (encaja, encaja_parcial, no_encaja), setting it apart from general comparison 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 usage is implied, meaning the agent knows it is used for evaluating fit. However, it does not explicitly state the necessary prerequisites, such as 'must be called after an offer has been fetched' or 'must have a previously constructed profile,' which would raise the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.