Jagent

Grade essays, check resumes, and ask typed yes/no, choice and rubric questions, powered by Jev.

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Calidad y seguridad

A
Calidad de la descripción
87%
Integridad del esquema
91%
Calidad de los nombres
83%
Riesgo de envenenamiento
100%
Coincidencia de permisos
100%
Cumplimiento del protocolo
100%

Hallazgos (1)

  • LOWTool 'judge_choice' description lacks action verben judge_choice

Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.

Costo de contexto

~1,499Tokens (definiciones de herramientas)
~1.6 KBTamaño de respuesta típico
Impacto moderado en la atención (1.17% del contexto de 128k)

Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.

Instalar

Instalación con un clic

Agrega esto a tu archivo `claude_desktop_config.json`:

{
  "mcpServers": {
    "jagent": {
      "url": "https://jev-agent.com/api/mcp"
    }
  }
}

Puntos de conexión remotos

https://jev-agent.com/api/mcpstreamable-http

Qué puede hacer

Inventario de herramientas

Herramientas (7)

🟢 Solo lectura🟡 Escritura🔴 Eliminación⚪ Desconocido
🟢check_resume(resume, job_description)

Score a resume, optionally against a job posting: a 0-100 match score, the posting's keywords found and missing (matched literally, as an ATS search would), ATS format checks, the level fit, and the probability a recruiter would move it to interview.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "resume": {
      "type": "string",
      "minLength": 150,
      "maxLength": 12000,
      "description": "The resume as plain text."
    },
    "job_description": {
      "description": "The job posting to match against. Omit for a general resume check.",
      "type": "string",
      "maxLength": 8000
    }
  },
  "required": [
    "resume"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢grade_essay(essay, kind, level, assignment, prompt, ...)

Grade one essay against a built-in rubric. kind "essay": six criteria and a letter grade, for class essays at middle school, high school or college level. kind "common-app": a Common App personal statement (pass the prompt number, 1-7). kind "sat": an SAT School Day essay, Reading/Analysis/Writing each 1-4 (pass the source passage to check quotations).

Esquema de entrada

{
  "type": "object",
  "properties": {
    "essay": {
      "type": "string",
      "minLength": 100,
      "maxLength": 20000,
      "description": "The essay text."
    },
    "kind": {
      "default": "essay",
      "type": "string",
      "enum": [
        "essay",
        "common-app",
        "sat"
      ]
    },
    "level": {
      "description": "kind \"essay\" only. Default high school.",
      "type": "string",
      "enum": [
        "middle school",
        "high school",
        "college"
      ]
    },
    "assignment": {
      "description": "kind \"essay\": the assignment prompt.",
      "type": "string",
      "maxLength": 2000
    },
    "prompt": {
      "description": "kind \"common-app\": which of the seven prompts. Default 7, topic of your choice.",
      "type": "integer",
      "minimum": 1,
      "maximum": 7
    },
    "passage": {
      "description": "kind \"sat\": the source passage.",
      "type": "string",
      "maxLength": 8000
    }
  },
  "required": [
    "essay"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢grade_with_rubric(criteria, points, submissions, assignment)

Grade one or more submissions (up to 30, in parallel) against a rubric you supply: each criterion scored on a 3- to 6-point scale, summed per submission. Each submission is graded in its own call, so its score never depends on the others.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "criteria": {
      "minItems": 1,
      "maxItems": 8,
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {
            "type": "string",
            "minLength": 1,
            "maxLength": 60
          },
          "description": {
            "type": "string",
            "maxLength": 300
          }
        },
        "required": [
          "name"
        ]
      },
      "description": "Rubric rows, e.g. { \"name\": \"Evidence\", \"description\": \"Supports the claim with specific evidence\" }."
    },
    "points": {
      "default": 4,
      "type": "integer",
      "minimum": 3,
      "maximum": 6
    },
    "submissions": {
      "minItems": 1,
      "maxItems": 30,
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {
            "type": "string",
            "maxLength": 80
          },
          "text": {
            "type": "string",
            "minLength": 100,
            "maxLength": 20000
          }
        },
        "required": [
          "text"
        ]
      }
    },
    "assignment": {
      "type": "string",
      "maxLength": 2000
    }
  },
  "required": [
    "criteria",
    "submissions"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢judge_yes_no(text, question, yes_means, no_means)

Ask any yes/no question about a text and get the probability that the answer is yes. Use for checks and gates, e.g. 'Does this reply answer the customer's question?'.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "minLength": 1,
      "maxLength": 60000,
      "description": "The text to judge."
    },
    "question": {
      "type": "string",
      "minLength": 3,
      "maxLength": 1000
    },
    "yes_means": {
      "description": "What a yes looks like, if it helps to spell out.",
      "type": "string",
      "maxLength": 300
    },
    "no_means": {
      "type": "string",
      "maxLength": 300
    }
  },
  "required": [
    "text",
    "question"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢judge_choice(text, question, options)

Pick the option that best fits a text, with a probability for every option and a confidence. Options map an id to a description of when it applies.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "minLength": 1,
      "maxLength": 60000
    },
    "question": {
      "type": "string",
      "minLength": 3,
      "maxLength": 1000
    },
    "options": {
      "type": "object",
      "propertyNames": {
        "type": "string",
        "minLength": 1,
        "maxLength": 60
      },
      "additionalProperties": {
        "type": "string",
        "minLength": 1,
        "maxLength": 500
      },
      "description": "e.g. { \"billing\": \"Payments, refunds, invoices\", \"technical\": \"Bugs and errors\" }"
    }
  },
  "required": [
    "text",
    "question",
    "options"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢judge_score(text, question, levels)

Place a text on an ordered scale you define (lowest level first) and get the nearest level, the exact position and a probability for each level.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "minLength": 1,
      "maxLength": 60000
    },
    "question": {
      "type": "string",
      "minLength": 3,
      "maxLength": 1000
    },
    "levels": {
      "minItems": 2,
      "maxItems": 10,
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1,
        "maxLength": 300
      },
      "description": "Lowest first, e.g. [\"Off-topic\", \"Partly relevant\", \"Fully relevant\"]."
    }
  },
  "required": [
    "text",
    "question",
    "levels"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢compare_versions(question, version_a, version_b, context)

Which of two versions is stronger for a stated purpose. Asked twice with the order swapped and averaged, because the model favors the second option on close calls; if the two orders disagree the result is a tie.

Esquema de entrada

{
  "type": "object",
  "properties": {
    "question": {
      "type": "string",
      "minLength": 3,
      "maxLength": 1000,
      "description": "e.g. 'Which opening line would an admissions reader find more compelling?'"
    },
    "version_a": {
      "type": "string",
      "minLength": 1,
      "maxLength": 5000
    },
    "version_b": {
      "type": "string",
      "minLength": 1,
      "maxLength": 5000
    },
    "context": {
      "description": "The surrounding text, such as the whole essay or the job posting.",
      "type": "string",
      "maxLength": 60000
    }
  },
  "required": [
    "question",
    "version_a",
    "version_b"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}

Comunidad

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Evidencia

Observaciones recientes

verificadoversión no registrada7 herramientas