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name swelist
description Find software engineering internships and new-grad jobs from SimplifyJobs; track and sync applications via Gmail, Notion, or local SQLite
homepage https://pypi.org/project/swelist/
metadata
openclaw
emoji requires install
💼
bins
swelist
id kind package bins label
uv
uv
swelist
swelist
Install swelist (uv)

swelist

This document defines the operational capabilities, invocation contract, and usage semantics of the swelist CLI tool for AI agents, schedulers, and automation systems.

Tool Identity

  • Name: swelist
  • Type: Command-Line Interface (CLI)
  • Language: Python
  • Distribution: PyPI
  • Execution Model: Stateless, read-only

Purpose

swelist retrieves recently added technology internship and new‑graduate job postings from curated public GitHub repositories and renders them in a predictable, text-based format.

It is optimized for: - Automation pipelines - Periodic polling agents - Human-in-the-loop job search workflows

Data Sources

  • SimplifyJobs / Summer2025-Internships
  • SimplifyJobs / New-Grad-Positions

Data is fetched live at runtime.

Installation

pip install swelist

Invocation Contract

swelist [--role ROLE] [--timeframe TIMEFRAME] [--location LOCATION]

The tool accepts only CLI flags. No stdin is consumed.

Parameters

--role

Controls which category of jobs to retrieve.

Value Meaning

internship Internship roles (default) newgrad New‑graduate roles

Example:

swelist --role newgrad

--timeframe

Controls recency filtering.

Value Time Window

lastday Last 24 hours lastweek Last 7 days lastmonth Last 30 days

Example:

swelist --timeframe lastweek

--location

Filters job postings by geographic location.

Input Meaning

Single location Canada or Toronto Multiple locations (comma-separated) "Boston, New York, Remote"

Example:

swelist --location Toronto
swelist --location "Boston, New York, Remote"

Output Contract

  • Output is written to STDOUT
  • Format is human- and agent-readable plain text
  • No JSON or structured serialization

Job Posting Fields

Each job entry contains:

  • Company (string)
  • Title (string)
  • Location (string)
  • Link (URL)

Example:

Company: Example Corp
Title: Software Engineer Intern
Location: Remote
Link: https://example.com/apply

Execution Guarantees

  • No side effects
  • No persistent storage
  • Safe for repeated execution
  • Deterministic given identical upstream data
  • No authentication required

Error Behavior

  • Network issues may raise runtime errors or result in empty output
  • Invalid flags produce CLI usage errors
  • Zero matching jobs produces valid empty result output

Environment Requirements

  • Python 3.8+
  • Internet access
  • Supported on macOS, Linux, Windows

Agent-Oriented Use Cases

  • Daily polling for new internship postings
  • Weekly new‑grad job aggregation
  • Feeding results into ranking, scoring, or alerting agents
  • Execution via cron, CI pipelines, or autonomous agents
  • Parsing job postings into structured JSON for downstream processing
  • Integration with AI agents for automated job application workflows

Known Limitations

  • No built‑in alerting
  • No local caching
  • No deduplication beyond source data
  • No JSON output format

Safety & Compliance

  • Uses only public data
  • No user tracking
  • No credential usage
  • No scraping of private systems

Versioning

Behavior may evolve with upstream data sources. CLI flags are considered stable within a major version.

jobgpt

This document defines the operational capabilities, invocation contract, and usage semantics of the jobgpt command for AI-powered job application assistance.

Tool Identity

  • Name: jobgpt
  • Type: Command-Line Interface (CLI)
  • Language: Python
  • Distribution: Part of swelist package
  • Execution Model: Stateless, AI-powered writing assistant

Purpose

jobgpt is an AI writing assistant that helps job seekers prepare for interviews and job applications by generating compelling answers and career advice.

It is optimized for: - Interview preparation - Application materials - Career guidance

Subcommands

ask

Ask any career or job-search question.

jobgpt ask "Your question here"

Parameters:

  • question (positional, required): Any job-search or career question

Options:

  • --model: OpenAI model to use (default: gpt-4o)
  • --copy: Copy output to clipboard (flag)

Example:

jobgpt ask "What should I focus on in my first internship?"
jobgpt ask "How do I negotiate salary?" --copy

why-company

Generate a compelling answer to "Why do you want to work at [Company]?"

jobgpt why-company "Company Name" --background "Your background"

Parameters:

  • company (positional, required): Company name

Options:

  • --background: Your background summary (optional, recommended)
  • --model: OpenAI model to use (default: gpt-4o)
  • --copy: Copy output to clipboard (flag)

Example:

jobgpt why-company "Google" --background "Software Engineering student with Python and web development experience"
jobgpt why-company "Meta" --background "Full-stack developer with React and Node.js expertise" --copy

behavioral

Generate a STAR-format answer to a behavioral interview question.

jobgpt behavioral "Question here" [--resume path/to/resume.txt]

Parameters:

  • question (positional, required): The behavioral interview question

Options:

  • --resume: Path to resume text file (optional)
  • --model: OpenAI model to use (default: gpt-4o)
  • --copy: Copy output to clipboard (flag)

Example:

jobgpt behavioral "Tell me about a time you dealt with conflict on a team"
jobgpt behavioral "Describe your biggest failure and how you learned from it" --resume resume.txt --copy

Output Contract

  • Output is written to STDOUT
  • Format is human-readable markdown with rich text formatting
  • Organized in clear panels with proper section headers
  • Optimized for reading and copying to clipboard

Execution Guarantees

  • Requires OpenAI API key (set via OPENAI_API_KEY environment variable)
  • No persistent storage
  • Safe for repeated execution
  • Deterministic given identical input (within model capabilities)

Error Behavior

  • Missing OPENAI_API_KEY environment variable produces clear error message
  • Invalid OpenAI model names produce API errors
  • Missing resume file produces OSError with clear message
  • Network issues may raise runtime errors

Environment Requirements

  • Python 3.8+
  • OpenAI API key (OPENAI_API_KEY)
  • Internet access for API calls
  • Supported on macOS, Linux, Windows

Agent-Oriented Use Cases

  • Preprocessing candidate data for interview coaching bots
  • Generating interview preparation materials at scale
  • Feeding career advice into autonomous career planning agents
  • Integration with resume builders and application workflows

Known Limitations

  • Requires OpenAI API key and internet connection
  • Responses vary based on model capability
  • No local caching of responses
  • No built-in follow-up question handling

Safety & Compliance

  • Uses only public OpenAI API
  • No data persistence
  • No credential sharing or exposure
  • Respects OpenAI usage policies

End of document.