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GitResume Agent ๐Ÿš€

PyPI Python CLI Multi--Agent Ollama Tests License: MIT

Autonomous Git-Driven Resume & Portfolio Agent
A zero-touch agentic pipeline that perceives git diffs and codebase ASTs upon commit, synthesizes grounded Google XYZ accomplishment bullets with adversarial critique, and autonomously compiles role-tailored resumes directly to production portfolio endpoints.


๐Ÿ’ก Why GitResume Agent?

As software and AI engineers, our codebases evolve every day โ€” we ship features, refactor parsers, optimize vector retrieval latencies, and increase test coverage. Yet, our resumes remain static, outdated, and ungrounded.

GitResume Agent automates the entire lifecycle of engineering credentials as an event-driven CI/CD system:

  1. Perception: Interrogates active Git repositories (commits, lines of code, test suites, and AST diffs) in < 5ms.
  2. Schema Discovery: Dynamically detects tech stack additions and hackathon track changes from README.md files and package manifests, updating configuration in-place.
  3. Reasoned Synthesis: Synthesizes quantified achievement bullets following the Google XYZ formula ("Accomplished X, measured by Y, by doing Z").
  4. Adversarial Critique: Validates every cited metric and library against the commit AST to mathematically eliminate hallucinations.
  5. Multi-Format Execution & Sync: Injects fresh bullets into Word (.docx) runs preserving exact styling, exports headless PDFs via COM automation, and syncs directly to your live portfolio website.

๐Ÿค– Truly Autonomous: How It Works

GitResume Agent operates on an event-driven, zero-touch autonomy loop:

                       โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
                       โ”‚           DEVELOPER ACTION          โ”‚
                       โ”‚          `git commit -m "..."`      โ”‚
                       โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                                          โ”‚
                                          โ–ผ (Post-Commit Hook Trigger)
 โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
 โ”‚                          AUTONOMOUS AGENT PIPELINE                               โ”‚
 โ”‚                                                                                  โ”‚
 โ”‚  1. PERCEPTION           2. SCHEMA DISCOVERY      3. REASONING & SYNTHESIS       โ”‚
 โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”    โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”    โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”   โ”‚
 โ”‚  โ”‚ InspectorAgent   โ”‚โ”€โ”€โ”€โ–ถโ”‚ SchemaDiscoverer โ”‚โ”€โ”€โ”€โ–ถโ”‚ SynthesizerAgent          โ”‚   โ”‚
 โ”‚  โ”‚ Git Log / AST    โ”‚    โ”‚ README & Badges  โ”‚    โ”‚ Flagship Ollama Cloud LLM โ”‚   โ”‚
 โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜    โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜    โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜   โ”‚
 โ”‚                                                                โ”‚                 โ”‚
 โ”‚                                                                โ–ผ                 โ”‚
 โ”‚  5. DUAL-TIER SYNC       4. COMPILATION           4. ADVERSARIAL CRITIQUE        โ”‚
 โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”    โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”    โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”   โ”‚
 โ”‚  โ”‚ Portfolio / Web  โ”‚โ—€โ”€โ”€โ”€โ”‚ Docx & PDF Engineโ”‚โ—€โ”€โ”€โ”€โ”‚ GroundingVerifierAgent    โ”‚   โ”‚
 โ”‚  โ”‚ Public Mirroring โ”‚    โ”‚ Headless Word COMโ”‚    โ”‚ AST / Metric Verification โ”‚   โ”‚
 โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜    โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜    โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜   โ”‚
 โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
  • Zero-Touch Git Hooks: Once installed, you never need to manually trigger compilation. Committing to any project repository automatically initiates background resume updates.
  • In-Place Schema Auto-Sync: Adding a new framework to package.json or a hackathon badge to README.md automatically mutates gitresume.yaml idempotently.
  • Deterministic Guardrails: Human governance controls initial role personas and target paths, while multi-agent execution handles perception, critique, and artifact compilation.

๐Ÿ—๏ธ Multi-Agent Architecture

Agent Roles:

  • SchemaDiscoverer Agent: Parses project README.md files, badges, and manifests (package.json, pyproject.toml, requirements.txt). When you add a tool or win a hackathon track, it updates gitresume.yaml in-place.
  • Inspector Agent: Interrogates git ls-files, git log, and test directories across 100K+ lines of code in < 5ms without traversal bottlenecks.
  • Synthesizer Agent: Employs flagship coding LLMs (e.g. kimi-k2.7-code, deepseek-v4-pro, qwen2.5-coder) via Ollama Cloud or local Ollama to craft high-impact accomplishment bullets.
  • Grounding Verifier Agent: Acts as an adversarial critic, verifying that cited frameworks and performance metrics are mathematically grounded in the git history.
  • Persona Dispatcher & Compilers: Modifies specific paragraph runs in Word .docx documents preserving exact typography, triggers MS Word COM automation for pixel-perfect PDF export, and syncs directly to public portfolio directories.

๐Ÿ“‚ Where Generated Resumes Are Stored & Synced

GitResume Agent manages a dual-tier storage system defined in your gitresume.yaml:

1. Primary Master Directory (output.resume_dir)

  • The primary folder where your master .docx templates and compiled .pdf files are stored.
  • Keeps all role-specific persona documents organized (e.g. Forward_Deployed_Engineer.docx, GenAI_Engineer.docx, AI_Engineer.docx, Master_Resume.docx).

2. Public Web / Portfolio Sync (output.sync_paths)

  • Mirrors compiled .docx and .pdf files directly to your live portfolio website (e.g. ./portfolio_site/public/resume), static site generator public folders, or CDN buckets.
  • Every time you run git-resume sync (or make a git commit), your live portfolio immediately serves the freshest resumes.

โšก Quickstart & Installation

1. Install via PyPI (Recommended)

pip install git-resume-agent
Or install from source (for contributors)

1. Clone & Install

git clone https://github.com/Naman6019/git-resume-agent.git
cd git-resume-agent

# Create virtual environment
python -m venv .venv
.venv\Scripts\activate      # Windows (or `source .venv/bin/activate` on Linux/macOS)

# Install editable package
pip install -e .

2. Configure Environment (Optional LLM Keys)

Copy .env.example to .env:

# Option A: Ollama Cloud (Uses flagship cloud models without local download)
OLLAMA_BASE_URL=https://ollama.com
OLLAMA_API_KEY=your_ollama_api_key

# Option B: Local Ollama (100% Free, Offline)
OLLAMA_BASE_URL=http://127.0.0.1:11434

# Option C: Google Gemini Free Endpoint
GEMINI_API_KEY=your_gemini_api_key

๐Ÿ•น๏ธ CLI Usage

1. Auto-Discover Schema from READMEs

Inspects configured repositories and syncs newly added tech tools or hackathon tags into gitresume.yaml:

git-resume auto-config

2. Install Zero-Touch Git Post-Commit Hooks

Automatically wires up post-commit hooks across all repositories listed in gitresume.yaml:

git-resume install-hooks

3. Live Codebase Intelligence Dashboard

Displays real-time commit counts, file statistics, total lines of code, and test suites across all tracked repositories:

git-resume scan

4. Synthesize Grounded Achievement Bullets

Uses multi-agent reasoning over recent git commits to generate role-specific Google XYZ bullets:

# Generate bullet for Forward-Deployed Engineer role
git-resume generate --repo MyProject --persona fde

# Generate bullet for Generative AI Engineer role
git-resume generate --repo MyProject --persona genai

# Generate bullet for AI/ML Engineer role
git-resume generate --repo MyProject --persona ai_engineer

5. Full End-to-End Multi-Agent Sync

Runs the entire pipeline (Inspect $\rightarrow$ Synthesize $\rightarrow$ Verify $\rightarrow$ Compile .docx $\rightarrow$ Export .pdf $\rightarrow$ Sync to Portfolio):

git-resume sync

โš™๏ธ Configuration (gitresume.yaml)

version: "1.0"

developer:
  name: "Your Name"
  email: "your.email@example.com"
  github: "https://github.com/yourusername"
  linkedin: "https://linkedin.com/in/yourprofile"
  location: "City, Country"

# Repositories to inspect & ground
repositories:
  - name: "EnterpriseAI"
    path: "./projects/EnterpriseAI"
    tag: "OpenAI Build Week Submission"
    primary_stack: ["Python", "FastAPI", "React", "TypeScript", "Qdrant", "PostgreSQL"]

  - name: "AgentOS"
    path: "./projects/AgentOS"
    tag: "Hackathon Track Submission"
    primary_stack: ["Python", "Google ADK", "LangGraph", "Next.js", "Firestore", "Google Cloud Run"]

# Resume Personas & Target Documents
personas:
  - id: "fde"
    title: "Agentic AI / Forward-Deployed Engineer"
    resume_file: "Your_Name_Agentic_AI_FDE_Resume.docx"
    emphasis: ["evals", "hybrid-search", "strict-abstention", "production-agents", "forward-deployed"]

  - id: "genai"
    title: "Generative AI Engineer"
    resume_file: "Your_Name_GenAI_Engineer_Resume.docx"
    emphasis: ["rag", "vector-embeddings", "langgraph", "llm-pipelines", "tool-calling"]

# Dual-Tier Storage & Compilation Targets
output:
  formats: ["docx", "pdf"]
  resume_dir: "./resumes"                     # Master storage directory
  sync_paths:
    - "./portfolio_site/public/resume"        # Public portfolio sync destination

# LLM Intelligence Engine
llm:
  provider: "ollama"
  model: "kimi-k2.7-code"
  fallback_model: "gpt-4o-mini"

๐Ÿช Zero-Touch Git Hook Integration

How does the automation work on every commit? When you run git-resume install-hooks (or python scripts/install_hooks.py):

  1. It reads your configured repository paths in gitresume.yaml.
  2. Locates each repository's .git/hooks/ folder.
  3. Installs an executable post-commit script that triggers git-resume sync in the background upon every commit.
git-resume install-hooks

Output:

๐Ÿ”ง Installing Git post-commit hooks...
  * โœ“ Installed hook for [EnterpriseAI]: ./projects/EnterpriseAI
  * โœ“ Installed hook for [AgentOS]: ./projects/AgentOS
โœ… Successfully installed hooks across 2 repositories!

๐Ÿงช Testing

Run the automated unit test suite:

pytest tests/ -v
collected 5 items
tests/test_git_resume.py::test_load_config PASSED        [ 20%]
tests/test_git_resume.py::test_inspector_agent PASSED    [ 40%]
tests/test_git_resume.py::test_grounding_verifier PASSED [ 60%]
tests/test_git_resume.py::test_synthesizer_agent PASSED  [ 80%]
tests/test_git_resume.py::test_schema_discoverer PASSED  [100%]
====================== 5 passed in 0.62s ======================

๐Ÿ“„ License

Distributed under the MIT License. See LICENSE for more information.


๐Ÿ‘ค Author

Naman Manocha โ€” @Naman6019

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