Project Chimera:Autonomous AI Influencer Platform

Project Chimera is a spec-driven repository that scaffolds an autonomous AI influencer platform: trend ingestion, content generation, safety reviews, and service integration (OpenClaw). This repo contains the technical and functional specifications, schema contracts, skill definitions, test harnesses, CI/CD workflows, and infrastructure scaffolding needed to develop, validate, and operate the agents.

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Overview

Project Chimera is designed to provide a production-ready, competition-level framework for autonomous AI agents. It ingests social trends, generates content variants, enforces skill contracts, validates against schemas, and maintains observability and governance through CI/CD pipelines.

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Project Structure

project-chimera-agent-factory/
├── README.md
├── LICENSE
├── specs/
│   ├── _meta.md
│   ├── functional.md
│   ├── technical.md
│   └── openclaw_integration.md
├── skills/
│   ├── skill_download_youtube/
│   │   └── HANDLER_PLACEHOLDER.md
│   ├── skill_transcribe_audio/
│   │   └── HANDLER_PLACEHOLDER.md
├── tests/
│   ├── conftest.py
│   ├── unit/
│   └── integration/
├── scripts/
│   └── validate_skill_contracts.py
├── alembic/
├── Dockerfile
├── Makefile
└── .github/
    └── workflows/

Target Audience

• AI/ML Engineers building autonomous agent systems.
• DevOps engineers managing CI/CD and containerized environments.
• Researchers exploring spec-driven agent architectures.
• Teams aiming for competition-level, production-ready Python projects.

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Prerequisites

• Python 3.11+
• Docker (optional but recommended)
• Git
• Basic understanding of:
  • OpenAPI
  • JSON Schema
  • Test-driven development

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Installation

Clone the repository:

git clone https://github.com/hydropython/project-chimera-agent-factory.git
cd project-chimera-agent-factory

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Environment Setup (uv)

This project uses uv for fast, reproducible Python environments:

uv venv
source .venv/bin/activate      # Windows: .\.venv\Scripts\activate
uv pip install -r requirements.txt

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Usage

Run Spec Validation

make spec-check

Validates:

• OpenAPI contracts
• JSON schemas
• Spec integrity

Run Skill Contract Validation

python src/validate_skill_contracts.py

Ensures:

• Skill inputs/outputs match schemas
• No undocumented interfaces exist

Run Tests (TDD)

make test

⚠️ Some tests may fail intentionally. This defines the agent’s required behavior.

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Data Requirements

• JSON inputs/outputs as defined in specs/ schemas.
• Video metadata stored in Postgres (see specs/db_schema.md).
• Skills input/output must conform to JSON schema contracts.

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Testing Strategy

• Tests are written before implementation (True TDD).
• Failing tests represent "empty slots" that agents must implement.
• Agents must conform to tests, not the other way around.

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Configuration

• CI/CD configuration: .github/workflows/main.yml
• AI co-pilot rules: CLAUDE.md
• AI review policy: .coderabbit.yaml
• Environment variables: .env (not committed)

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Methodology

Project Chimera follows these principles:

• Specification First
• Schemas as Law
• Tests as Contracts
• Skills as Capabilities
• Governance over Freedom

No code is written without specs.
No specs exist without validation.

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Performance Expectations

• Schema validation: milliseconds
• Skill contract checks: milliseconds
• CI execution: < 5 minutes
• Docker image: minimal, deterministic

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Containerization

Build the Docker image:

make build-image

Run inside Docker:

docker run chimera-agent-factory

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CI/CD & Governance

• CI runs on every push and PR:
  • Spec validation
  • Skill contract validation
  • Test execution
• AI governance rules enforce:
  • Spec alignment
  • Security hygiene
  • No undocumented behavior

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Security

• Secrets are never committed.
• Key management via external KMS is recommended.
• .coderabbit.yaml checks for insecure patterns.

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Contributing

• Read CLAUDE.md (Prime Directive)
• Reference specs in every PR
• Add or update tests
• Keep commits small and reviewable
• PRs without spec alignment will be rejected

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License

See the top-level LICENSE file for full license terms.

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Changelog

See Git commit history for versioned changes.

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Citation

If you use this project in academic work, cite via:

Project Chimera — Hydropython Team, 2026. Repository: https://github.com/hydropython/project-chimera-agent-factory

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Contact

• Repository owner: see Git history and remote origin
• Issues: open GitHub issues in this repository

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Architecture Diagram

flowchart LR
  subgraph External
    A["Social Platforms\n(Twitter, Reddit, YouTube, Google Trends)"]
    B["OpenClaw Network"]
    H["Human Reviewers"]
  end

  subgraph Chimera_Core
    TF["Trend Fetcher"]
    TA["Trend Analyzer"]
    CG["Content Generator"]
    SL["Safety Layer"]
    SK["Skills Runtime"]
    RG["Registry / Integration"]
    DB["Metadata DB"]
    CACHE["Cache / Vector DB"]
    OBS["Observability / Tracing"]
  end

  A -->|signals| TF
  TF --> TA
  TA --> DB
  TA --> CG
  CG --> SL
  SL -->|queue| H
  H -->|decision: approve or reject| SL
  SL -->|publish| RG
  RG -->|register or discover| B
  RG --> SK
  SK --> CG
  CG --> DB
  DB --> CACHE
  TF --> OBS
  TA --> OBS
  CG --> OBS
  RG --> OBS

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