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Parse Resume Document

civify_parse_cv

Parse a resume document (PDF, DOCX, image) into structured JSON schema containing contact details, work experience, education, skills, and projects. May consume AI credits; do not automatically retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileNoA user-selected chat attachment supplied by the client. Never invent a download URL or file ID.
file_urlNoActual HTTPS download URL supplied by the client or user. Never use a sandbox path, file ID alone or an invented URL.
filenameNoOriginal filename for base64 data, including extension (PDF, DOCX, PNG or JPG). Inferred from bytes when omitted.
languageNoLanguage code (e.g. 'en', 'ar', 'auto'). Default is 'auto'.auto
file_base64NoBase64 encoded content of the resume document (PDF, DOCX). Recommended for remote/cloud MCP servers.
resume_textNoComplete resume text read from the attachment. Preferred fallback when the client cannot forward bytes. Do not summarize or invent missing content.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / properties / api_key
      Removed value: -{
      -  "description": "Optional API key override.",
      -  "type": "string"
      -}
  2. Changed20 schema fields changed
    • changedInput schema / anyOf
      Previous value: -[
      -  {
      -    "required": [
      -      "resume_text"
      -    ]
      -  },
      -  {
      -    "required": [
      -      "file_base64"
      -    ]
      -  },
      -  {
      -    "required": [
      -      "server_file_path"
      -    ]
      -  }
      -]New value: +[
      +  {
      +    "required": [
      +      "resume_text"
      +    ]
      +  },
      +  {
      +    "required": [
      +      "file_base64"
      +    ]
      +  },
      +  {
      +    "required": [
      +      "file"
      +    ]
      +  },
      +  {
      +    "required": [
      +      "file_url"
      +    ]
      +  }
      +]
    • addedInput schema / properties / file
      Added value: +{
      +  "additionalProperties": false,
      +  "description": "A user-selected chat attachment supplied by the client. Never invent a download URL or file ID.",
      +  "properties": {
      +    "download_url": {
      +      "type": "string"
      +    },
      +    "file_id": {
      +      "type": "string"
      +    },
      +    "file_name": {
      +      "type": "string"
      +    },
      +    "mime_type": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "download_url",
      +    "file_id"
      +  ],
      +  "type": "object"
      +}
    • addedInput schema / properties / file_url
      Added value: +{
      +  "description": "Actual HTTPS download URL supplied by the client or user. Never use a sandbox path, file ID alone or an invented URL.",
      +  "type": "string"
      +}
    • removedInput schema / properties / filename / default
      Removed value: -"resume.pdf"
    • changedInput schema / properties / filename / description
      Previous value: -"Filename when providing base64 (e.g., 'resume.pdf')."New value: +"Original filename for base64 data, including extension (PDF, DOCX, PNG or JPG). Inferred from bytes when omitted."
    • changedInput schema / properties / resume_text / description
      Previous value: -"Plain text or markdown content of the resume. Easiest option when chatting with an AI agent."New value: +"Complete resume text read from the attachment. Preferred fallback when the client cannot forward bytes. Do not summarize or invent missing content."
    • addedInput schema / properties / resume_text / minLength
      Added value: +1
    • removedInput schema / properties / server_file_path
      Removed value: -{
      -  "description": "Local file path on the MCP server machine. For local CLI/stdio usage only. In ChatGPT or Claude, pass 'resume_text' or 'file_base64' instead.",
      -  "type": "string"
      -}
    • removedOutput schema / properties / contact
      Removed value: -{
      -  "description": "Candidate contact information (name, email, phone, location, links)",
      -  "type": "object"
      -}
    • addedOutput schema / properties / data
      Added value: +{}
    • removedOutput schema / properties / detectedLanguage
      Removed value: -{
      -  "description": "Primary detected language code (e.g., 'en', 'ar')",
      -  "type": "string"
      -}
    • removedOutput schema / properties / education
      Removed value: -{
      -  "description": "Academic degrees and certifications",
      -  "items": {
      -    "type": "object"
      -  },
      -  "type": "array"
      -}
    • removedOutput schema / properties / experience
      Removed value: -{
      -  "description": "Chronological employment history",
      -  "items": {
      -    "type": "object"
      -  },
      -  "type": "array"
      -}
    • removedOutput schema / properties / message
      Removed value: -{
      -  "description": "Diagnostic or status message",
      -  "type": "string"
      -}
    • removedOutput schema / properties / projects
      Removed value: -{
      -  "description": "Key projects and achievements",
      -  "items": {
      -    "type": "object"
      -  },
      -  "type": "array"
      -}
    • removedOutput schema / properties / resumeData
      Removed value: -{
      -  "description": "Parsed resume sections including contact, experience, education, skills, and projects",
      -  "type": "object"
      -}
    • removedOutput schema / properties / skills
      Removed value: -{
      -  "description": "Technical and domain skills extracted",
      -  "items": {
      -    "type": "string"
      -  },
      -  "type": "array"
      -}
    • removedOutput schema / properties / success
      Removed value: -{
      -  "description": "Whether the document was successfully parsed",
      -  "type": "boolean"
      -}
    • removedOutput schema / properties / summary
      Removed value: -{
      -  "description": "Professional summary statement",
      -  "type": "string"
      -}
    • addedOutput schema / required
      Added value: +[
      +  "data"
      +]
  3. Changed3 schema fields changed
    • changedInput schema / anyOf
      Previous value: -[
      -  {
      -    "required": [
      -      "resume_text"
      -    ]
      -  },
      -  {
      -    "required": [
      -      "file_base64"
      -    ]
      -  },
      -  {
      -    "required": [
      -      "file_path"
      -    ]
      -  }
      -]New value: +[
      +  {
      +    "required": [
      +      "resume_text"
      +    ]
      +  },
      +  {
      +    "required": [
      +      "file_base64"
      +    ]
      +  },
      +  {
      +    "required": [
      +      "server_file_path"
      +    ]
      +  }
      +]
    • removedInput schema / properties / file_path
      Removed value: -{
      -  "description": "Local file path on the MCP server machine. Do NOT use for remote cloud servers; use 'resume_text' or 'file_base64' instead.",
      -  "type": "string"
      -}
    • addedInput schema / properties / server_file_path
      Added value: +{
      +  "description": "Local file path on the MCP server machine. For local CLI/stdio usage only. In ChatGPT or Claude, pass 'resume_text' or 'file_base64' instead.",
      +  "type": "string"
      +}
  4. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the mutation profile is known. The description adds valuable behavioral context beyond annotations: it may consume AI credits and should not be automatically retried. This is a meaningful operational caveat that the annotations cannot express. The description does not detail failure behavior or rate limits, but the credit warning is a strong addition.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the verb and resource, lists the key input and output specifics, and ends with a critical behavioral caveat. Every word earns its place; there is no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, nested objects, multiple input modes, output schema exists), the description plus the schema provides sufficient context for correct invocation. The AI-credit warning and retry policy are critical and included. The only small gap is not explicitly mentioning an entitlement prerequisite, but that is covered by sibling tools and not necessary for invoking this specific tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with detailed parameter descriptions, so the schema carries the semantic load. The tool description adds summary-level context (input formats, output fields) but does not repeat parameter details unnecessarily. The strong schema coverage including warnings like 'never invent a download URL' justifies a score above baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb ('Parse'), a resource ('resume document'), and the output ('structured JSON schema containing contact details, work experience, education, skills, and projects'). This distinguishes it from siblings like civify_score_ats or civify_tailor_cv, whose names and purposes are clearly different.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description lists supported input formats (PDF, DOCX, image) and the output structure, which implies when this tool is appropriate. The schema's anyOf provides clear alternatives for input modes (resume_text, file_base64, file, file_url). The warning 'do not automatically retry' adds operational guidance. However, it does not explicitly state when to prefer this over alternatives like scoring or tailoring, though the purpose difference is self-evident.

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

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