JSON schema: extract a resume

JSON Schema to extract a resume with an LLM: experience, skills, education and certifications. Leaves out age, photo and other protected data.

Extract the resume data. Invent nothing: if information is missing, leave the field empty. Never infer age, race, religion, national origin, marital status, pregnancy or disability: these are protected characteristics under U.S. equal employment law.

JSON Schema

{
  "type": "object",
  "required": [
    "name",
    "experience",
    "skills"
  ],
  "properties": {
    "name": {
      "type": "string"
    },
    "skills": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "headline": {
      "type": "string",
      "description": "Current or target job title"
    },
    "education": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "year": {
            "type": "string"
          },
          "degree": {
            "type": "string"
          },
          "school": {
            "type": "string"
          }
        }
      }
    },
    "experience": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "title",
          "company"
        ],
        "properties": {
          "end": {
            "type": "string"
          },
          "start": {
            "type": "string"
          },
          "title": {
            "type": "string"
          },
          "company": {
            "type": "string"
          }
        }
      }
    },
    "certifications": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "years_of_experience": {
      "type": "number"
    }
  }
}

Costo stimato

Token di input per chiamata : ≈ 554

Solo costo di input, esclusa la risposta del modello. Prezzi pubblici standard dei fornitori (Mistral AI, DeepSeek, OpenAI, Anthropic) convertiti da USD in euro al cambio BCE del 29 settembre 2026. Stima: 1 token ≈ 3,6 caratteri.

Identificativo

contextetech--extract-resume

Tipo

Schemi di output

File

extract-resume.schema.json

Formato

JSON (application/json)

Dimensione

1292 byte (1,3 KB)

Codifica

UTF-8

Token stimati

≈ 359

Lingua

Inglese

Licenza

MIT

Uso commerciale

Consentito

Dati personali

Nessuno

Versione

1.0

Pubblicato il

2 ottobre 2026 alle ore 21:54

Aggiornato il

2 ottobre 2026 alle ore 21:54

Archiviazione

nel database

Utilizzi

0

Mi piace

0

extract-resume.schema.json

{
  "type": "object",
  "required": [
    "name",
    "experience",
    "skills"
  ],
  "properties": {
    "name": {
      "type": "string"
    },
    "skills": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "headline": {
      "type": "string",
      "description": "Current or target job title"
    },
    "education": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "year": {
            "type": "string"
          },
          "degree": {
            "type": "string"
          },
          "school": {
            "type": "string"
          }
        }
      }
    },
    "experience": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "title",
          "company"
        ],
        "properties": {
          "end": {
            "type": "string"
          },
          "start": {
            "type": "string"
          },
          "title": {
            "type": "string"
          },
          "company": {
            "type": "string"
          }
        }
      }
    },
    "certifications": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "years_of_experience": {
      "type": "number"
    }
  }
}

API Anthropic (Python)

import json, anthropic

schema = json.load(open("extract-resume.schema.json"))
client = anthropic.Anthropic()
resp = client.messages.create(model="claude-sonnet-5", max_tokens=1024,
    tools=[{"name": "extraire", "description": "Renvoie les données extraites", "input_schema": schema}],
    tool_choice={"type": "tool", "name": "extraire"},
    messages=[{"role": "user", "content": "il tuo input qui"}])
print(resp.content[0].input)

Formato OpenAI (response_format)

{
  "type": "json_schema",
  "json_schema": {
    "name": "extract-resume",
    "schema": {
      "type": "object",
      "required": [
        "name",
        "experience",
        "skills"
      ],
      "properties": {
        "name": {
          "type": "string"
        },
        "skills": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "headline": {
          "type": "string",
          "description": "Current or target job title"
        },
        "education": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "year": {
                "type": "string"
              },
              "degree": {
                "type": "string"
              },
              "school": {
                "type": "string"
              }
            }
          }
        },
        "experience": {
          "type": "array",
          "items": {
            "type": "object",
            "required": [
              "title",
              "company"
            ],
            "properties": {
              "end": {
                "type": "string"
              },
              "start": {
                "type": "string"
              },
              "title": {
                "type": "string"
              },
              "company": {
                "type": "string"
              }
            }
          }
        },
        "certifications": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "years_of_experience": {
          "type": "number"
        }
      }
    },
    "strict": true
  }
}