Skip to main content

Project Classified — Web3-native AI agent runtime for PyVax. Build + deploy resilient agents in 60s.

Project description

🧪 Classified Agent — Synthesis Hackathon CLI

PyPI version Python 3.10+ License: MIT

Build + submit AI agents for Synthesis Hackathon ($75K prizes) in 60 seconds.

100% offline core. PyVax-powered Web3 scaffolding. Resilient state machine with automatic resume.


⚡ Quickstart (60 seconds to submission)

pip install classified-agent

classified-agent init
# → Creates classified.toml, agent.yaml, SKILL.md, workspace/, logs/, examples/

# Edit classified.toml (set API keys)
export ANTHROPIC_API_KEY='sk-ant-...'

classified-agent doctor
# → Verifies environment readiness (10 checks)

classified-agent run
# 🚀 Agent running!

🏗️ Architecture

classified_agent/
├── cli/             # Typer CLI: init, doctor, run, join-synthesis
├── config/          # Pydantic v2 models + TOML loader
├── core/            # Agent runtime (LLM, loop, context, memory)
├── tools/           # 14 built-in tools (fs, http, git, web3)
├── wallet/          # On-chain backends (PyVax local, mock, managed)
├── adapters/        # Synthesis.md hackathon integration
├── logging/         # Rich console + JSONL structured logs
├── templates/       # Scaffold assets for init (skills, examples, prompts)
├── examples/        # Example classified.toml configurations
└── tests/           # pytest test suite

🎯 CLI Commands

Command Description
classified-agent init Scaffold config + workspace + skills + examples
classified-agent doctor Verify environment readiness (10 checks)
classified-agent run Start the agent loop
classified-agent run --dry-run Simulate (no on-chain txs)
classified-agent run --verbose Debug-level logging
classified-agent join-synthesis --enable Join Synthesis hackathon mode

🔧 Configuration (classified.toml)

[agent]
name = "my-agent"
max_steps = 50
workspace_dir = "./workspace"

[llm]
provider = "anthropic"        # "anthropic" | "openai"
model = "claude-sonnet-4-20250514"
api_key_env = "ANTHROPIC_API_KEY"

[wallet]
backend = "pyvax_local"       # "pyvax_local" | "mock"
default_chain = "avalanche_fuji"

[wallet.policy]
max_native_per_tx = "0.1"     # AVAX per transaction
max_native_per_day = "1.0"    # daily spend cap

[synthesis]
enabled = false
track = "open"                # open | uniswap | base | lido

🛠️ Built-in Tools (14 + 3 Synthesis)

Category Tools
Filesystem fs_read, fs_write, fs_list
HTTP http_get (domain allowlist)
Git git_init, git_status, git_commit
PyVax pyvax_compile, pyvax_deploy, pyvax_call
Wallet wallet_get_balance, wallet_send_native, wallet_erc20_transfer, wallet_erc20_approve
Synthesis synthesis_load_skill, synthesis_register, synthesis_report_status

🔒 Safety & Resilience

  • Wallet Policy: Per-tx and daily spend caps, contract/method allowlists
  • Sandboxed FS: All file ops confined to workspace directory
  • HTTP Allowlist: Only whitelisted domains (synthesis.md, pyvax.xyz, GitHub, Avalanche)
  • Dry-Run Mode: --dry-run flag simulates all state-changing operations
  • API Resilience: Exponential backoff + retry for rate limits
  • State Checkpoints: Resume from exact failure point

🏆 Synthesis Hackathon Workflow

1. pip install classified-agent==1.2.1
2. classified-agent init
3. Set API keys in .env or export them
4. classified-agent doctor
5. classified-agent run  (or  join-synthesis --enable)
6. Agent reads SKILL.md → plans → acts → observes → done

📖 Skill Files

Project Classified bundles a SKILL.md that teaches agents how to operate:

  • Agent identity and capabilities
  • How to read classified.toml
  • How to use the wallet safely
  • Available tools and usage rules
  • How to log actions
  • How to execute missions

Copied to your project root during init. Edit to customise agent behaviour.

📦 Development

git clone https://github.com/ShahiTechnovation/classified-agent
cd classified-agent
pip install -e ".[dev]"
pytest classified_agent/tests/ -v

🔗 Links

License

MIT — see LICENSE

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

classified_agent-1.3.0.tar.gz (76.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

classified_agent-1.3.0-py3-none-any.whl (94.4 kB view details)

Uploaded Python 3

File details

Details for the file classified_agent-1.3.0.tar.gz.

File metadata

  • Download URL: classified_agent-1.3.0.tar.gz
  • Upload date:
  • Size: 76.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for classified_agent-1.3.0.tar.gz
Algorithm Hash digest
SHA256 3826c94e336d1cedb25e964c32f252d26eec4ef02cf042b213cf19c2ccb96bd1
MD5 e42be50bf3323037e745272f3480471a
BLAKE2b-256 2da7222f4e9e6ab8ca76de180c2f7dd29c53dffa73662662a3467fffc8a3affe

See more details on using hashes here.

File details

Details for the file classified_agent-1.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for classified_agent-1.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 be2a7cce51bde343355111985cba4cbfe1e7e27a5c61d81f655e435d7db638fa
MD5 170c88acca9d835073e0a06bce82bc91
BLAKE2b-256 73828be4f130c2e3ae87335c345e4627fef6d24947b1637aa23108a95ea0ca3c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page