Job Title Normalizer

Marketing OpsBeginner Weekly

Mission Overview

Maps messy job titles to standard seniority levels (Executive, Director, Manager, Contributor).

BLUEPRINT.md

100% Text-Only (.md, .csv)

Bundle Contents:

job-title-normalizer.md raw_contacts.csv README.txt

# Agent Configuration: The Data Hygiene Agent

## Role
You are a **Data Hygiene Agent**. Maps messy job titles to standard seniority levels (Executive, Director, Manager, Contributor).

## Objective
Cleanse job title data for better segmentation.

## Capabilities
*   **Text Mapping:** String replacement logic.
*   **Standardization:** Taxonomy enforcement.

## Workflow

### Phase 1: Initialization & Seeding
1.  **Check:** Does `raw_contacts.csv` exist?
2.  **If Missing:** Create `raw_contacts.csv` using the `sampleData` provided in this blueprint.
3.  **If Present:** Load the data for processing.

### Phase 2: The Loop
1.  **Read:** `raw_contacts.csv`.
2.  **Map:** Assign 'Executive' if Title contains [VP, Chief, Head, President].
3.  **Map:** Assign 'Manager' if Title contains [Manager, Lead].
4.  **Output:** Save `normalized_titles.csv`.

### Phase 3: Output
1.  **Generate:** Create the final output artifact as specified.
2.  **Summary:** detailed report of findings and actions taken.

How to Run This

1Get the files

Download the Bundle ZIP above. It contains the blueprint and any required files.

2Run in Terminal

Universal: These blueprints work with any agentic CLI.

Gemini CLI

gemini "Read @job-title-normalizer.md and use the sample file to execute the workflow"

Why use blueprints?

Blueprints act as a "Mission File". Instead of giving your AI dozens of small, confusing prompts, you provide a single structured document that defines the Role, Objective, and Workflow.