feat(templates): add Automated HR Screener template

[vakrahul]

🐝 Add Automated HR Screener Agent Template

Summary

issue- #5302

A complete 5-node agent template that screens PDF resumes against a job description, scores and ranks candidates 1–100, generates a plain text report, and optionally sends response emails via Resend.

Pipeline

intake → scan-resumes → rank-candidates → generate-report → notify-candidates

Features

• Multi-provider LLM support — Works with Anthropic, Groq, Gemini, HuggingFace, Cerebras, DeepSeek, OpenRouter, Together AI, and local Ollama models via LiteLLM
• Privacy-first design — All resume processing runs locally; PII never leaves the machine unless email notifications are opted in
• Python-based input collection — Job description, resume path, and email preference collected via reliable Python prompts before TUI launch (bypasses LLM intake unreliability)
• Plain text reports — Generates structured, readable hr_screening_report.txt with candidate rankings and recommendations
• Email notifications — Optional candidate emails via Resend API with user approval before sending
• Interactive TUI — Full Textual-based dashboard with graph visualization, streaming output, and session management
• Resend API key prompt — Prompts for Resend key at startup if not set in environment

Scoring Criteria

Criterion	Weight
Skills Match	40%
Experience	25%
Education	15%
Communication	10%
Bonus Factors	10%

Files

File	Purpose
nodes/__init__.py	5 node definitions with system prompts
agent.py	Graph construction, edges, goal, constraints
__main__.py	CLI entry point with TUI, shell, and headless modes
config.py	Runtime configuration and agent metadata
agent.json	Serialized agent spec for tooling/inspection
README.md	Full documentation with multi-provider setup guide

Usage

# Set your API key
export Any cloud Api key=your-key-here

# Run the TUI
python -m examples.templates.hr_screener tui

Constraints (Hard)

• Never fabricate resume content or scores
• Never transmit raw resume content externally
• Never send emails without explicit user approval
• Apply scoring criteria consistently across all candidates

[github-actions]

PR Closed - Requirements Not Met

This PR has been automatically closed because it doesn't meet the requirements.

Missing: No linked issue found.

To fix:

1. Create or find an existing issue for this work
2. Assign yourself to the issue
3. Re-open this PR and add Fixes #123 in the description

Exception: To bypass this requirement, you can:

• Add the micro-fix label or include micro-fix in your PR title for trivial fixes
• Add the documentation label or include doc/docs in your PR title for documentation changes

Micro-fix requirements (must meet ALL):

Qualifies	Disqualifies
< 20 lines changed	Any functional bug fix
Typos & Documentation & Linting	Refactoring for "clean code"
No logic/API/DB changes	New features (even tiny ones)

Why is this required? See #472 for details.

[bryanadenhq]

Hey @vakrahul, here are some requested changes