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upload-job-file

Upload PDF, DOCX, or TXT job description files to extract structured data including job titles, requirements, qualifications, and company details.

Instructions

Upload a job description file (PDF, DOCX, TXT) as base64-encoded content and parse it into structured job data. Returns extracted job title, requirements, qualifications, and company info. Use this when the job description is in a file rather than plain text. Max file size ~10 MB. Requires scope: upload:write. For plain text or URL-based job descriptions, use upload-job-text instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileBase64YesBase64-encoded file content (PDF, DOCX, etc.) — max ~10 MB
filenameYesOriginal filename with extension
contentTypeNoMIME type
Behavior4/5

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

No annotations provided, so description carries full burden. It successfully discloses: auth requirement ('Requires scope: upload:write'), size constraint ('Max file size ~10 MB'), and return value structure (extracted title, requirements, etc.). Minor gap: doesn't clarify if the uploaded file persists as a stored resource or is transiently processed.

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?

Four dense sentences with zero waste. Front-loaded with core operation, followed by return values, usage conditions, and constraints/alternatives. Every sentence earns its place.

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?

Strong coverage given no output schema: describes extracted return fields, size limits, auth scope, and sibling alternatives. Only minor gap is ambiguity around whether the upload creates a persistent stored resource or is purely for extraction.

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 coverage is 100%, establishing baseline 3. Description adds valuable semantic context: specifies allowed formats (PDF/DOCX/TXT) which informs filename/contentType usage, reinforces base64 encoding requirement, and links maxLength to the ~10 MB constraint mentioned in description.

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?

Excellent specificity: verb (upload) + resource (job description file) + formats (PDF/DOCX/TXT) + transformation (parse into structured data). Explicitly distinguishes from sibling 'upload-job-text' by contrasting file-based vs plain text inputs.

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

Usage Guidelines5/5

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

Explicit when-to-use ('when the job description is in a file rather than plain text') and when-not-to-use with named alternative ('For plain text or URL-based job descriptions, use upload-job-text instead'). Also notes prerequisite scope requirement.

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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