Skip to main content
Glama

upload-job-text

Parse job descriptions from plain text or URLs to extract structured data including titles, requirements, and qualifications.

Instructions

Parse a job description from plain text or fetch and parse from a URL. Returns structured job data including title, requirements, and qualifications. Use this when you have the job description as text or a URL to a job posting page. At least one of text or url is required. Requires scope: upload:write. For file-based job descriptions (PDF, DOCX), use upload-job-file instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoJob description text (max 50K characters). Required if url is not provided.
urlNoURL to fetch job description from. Required if text is not provided.
sourceNoSource label/identifier for the job posting
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses output structure ('structured job data including title, requirements, and qualifications'), authentication scope, and input validation constraints ('At least one of text or url is required'). Missing explicit idempotency or side-effect details.

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?

Six sentences, front-loaded with action (parse/fetch), followed by return values, usage context, constraints, auth requirements, and sibling distinction. Zero waste.

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

Completeness5/5

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

No output schema exists, but description adequately explains return values. Distinguishes from sibling upload-job-file. Given 100% schema coverage and moderate param count (3), description is complete.

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 has 100% description coverage (baseline 3). Description adds value by clarifying the cross-parameter requirement constraint ('At least one of text or url is required') that the schema enforces only in individual field descriptions, not at the object level.

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?

Specific verb+resource ('Parse a job description'/'fetch and parse'), distinguishes from sibling 'upload-job-file' via explicit recommendation for PDF/DOCX files, and clearly states the dual input methods (text vs URL).

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 you have the job description as text or a URL'), explicit alternative named ('use upload-job-file instead'), and discloses authentication prerequisite ('Requires scope: upload:write').

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ebenezer-isaac/llmconveyors-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server