Skip to main content

🏗️ SILO Framework

S.I.L.O (Secure. Isolated. Lightweight. Offloaded.) helps developers bring their ideas to life by conquering the complexity of AI tool execution. It provides a trusted tool ecosystem for AI Agents—ensuring tools are invoked safely, reliably, and with zero configuration headache.

License: MIT Python 3.9+ MCP Ready Docs

📖 Read the Documentation (or browse docs/index.md) for a trusted starting point on writing skills, security, and deploying as an MCP server.


🔥 Why SILO?

Most "AI Skills" today are just unstructured text prompts telling an agent to "be smart" and write code on the fly to solve a problem. This works for simple tasks, but falls apart when you need reliable, repeatable, and secure integrations.

The Problem

  • Token Leaks: Passing API keys in prompts or CLI arguments is a massive security risk.
  • Dependency Hell: Each skill needs its own .venv, requirements.txt, and setup.
  • LLM Hallucinations: Agents struggle with unstructured text or unclear argument types.
  • Complexity: Writing a full MCP server or a robust CLI wrapper takes too much boilerplate.

The SILO Solution

SILO is built on four core pillars:

  • 🔒 Secure: Tokens or keys never reach the LLM context. In SILO, secrets live in your OS Keychain or Env, keeping them invisible to the model and the logs.
  • 📦 Isolated: Each skill is a self-contained module. With uv (PEP 723) support, a single file can manage its own dependencies without polluting your global environment.
  • 🪶 Lightweight: Skill instructions (SKILL.md) are minimalist and focused. A skill should solve one clearly defined task with maximum clarity.
  • ⚡ Offloaded: Perform as much work as possible procedurally (in Python) rather than through the LLM. This saves tokens, reduces cognitive load on the agent, and ensures predictable, accurate results.

🚀 The SILO Workflow: How it Works

SILO transforms the development of AI tools into a streamlined 4-step process.

1. Scaffolding

Start with a single command to generate a compliant skill template.

silo init github-skill --secrets GITHUB_TOKEN

This creates a folder named github-skill with a PEP 723 compliant skill.py, ensuring uv can run it with all necessary dependencies (including silo-framework itself) in a temporary, isolated environment.

2. Development (The Code)

Define your commands using standard Python functions and Pydantic models. SILO handles the rest—argument parsing, JSON serialization, and error handling.

from silo import Skill, require_secret, AgentResponse
from pydantic import BaseModel

app = Skill("github")

class Issue(BaseModel):
    title: str
    body: str

@app.tool()
def create_issue(repo: str, detail: Issue):
    """Creates a new issue in a repository."""
    # This NEVER leaks to the LLM. 
    # It fetches from Keychain, Env, or prompts via browser.
    token = require_secret("GITHUB_TOKEN") 
    
    # Procedural logic (Offloaded from LLM)
    return AgentResponse(
        llm_text=f"Successfully created issue '{detail.title}' in {repo}",
        raw_data={"status": "created", "repo": repo, "issue_id": 123}
    )

if __name__ == "__main__":
    app.run()

3. Verification (silo test)

Agents don't have a terminal (TTY). They don't have a display. They need clean, predictable output.

silo test github_skill.py create_issue --repo "user/repo" --detail '{"title": "Bug", "body": "Fixed"}'

silo test runs your skill in a simulated "headless agent" environment, verifying that:

  • The manifest generates correctly.
  • Authentication fallbacks trigger properly.
  • Output is valid JSON/Markdown.

4. Deployment & MCP Export

Want to use this skill in Claude Desktop? You don't need to rewrite a single line. Just change one method call:

if __name__ == "__main__":
    # app.run()     <-- Standard CLI
    app.run_mcp()   <-- Instant MCP tool server!

🛠️ Advanced Features

🔐 Headless-Friendly Auth

When a skill needs a secret but there is no terminal (standard for agents), SILO:

  1. Checks os.environ.
  2. Checks the OS Keychain (macOS, Windows, Linux).
  3. If missing and a display is detected, it opens a local browser tab with a secure dark-mode form for the user to input the token. The token is saved to the keychain and aldrig passed to the agent.

🩺 Environment Doctor

Not sure if your system is ready for S.I.L.O?

silo doctor

Checks for Python version, uv presence, Keychain accessibility, and critical dependencies.


📜 License

MIT © Timur Pitsunov

Metadata

Release files for silo-framework 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for silo-framework 0.1.1
File Size Uploaded Provenance Actions
silo_framework-0.1.1.tar.gz 221.0 kB With provenance Details for silo_framework-0.1.1.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for silo-framework 0.1.1
File Interpreter ABI Platform Actions
silo_framework-0.1.1-py3-none-any.whl Python 3 none any Details for silo_framework-0.1.1-py3-none-any.whl

Total release size: 253.8 kB

Release files / silo_framework-0.1.1.tar.gz

Download URL silo_framework-0.1.1.tar.gz
Size 221.0 kB
Tags Source
SHA-256 checksum
How to use checksums
da3056ed74f99f67c921e1f3d16f5a0c7d0a2c714a6d43238b4ddee09b71ded1
BLAKE2b-256 checksum
How to use checksums
a351750c278f892c9a744f2c4c979be5860c999a899a250c773a5794dd5ad31b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Mar 17, 2026.

Transparency log

Release files / silo_framework-0.1.1-py3-none-any.whl

Download URL silo_framework-0.1.1-py3-none-any.whl
Size 32.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
799da2d88e129c46c9414535ba17cbd3e25f485427bc06c853bae00781b52bbc
BLAKE2b-256 checksum
How to use checksums
5a1e7714b63c0038e9223c085621107a110e02f08a75a9cdae8d3aba86201c9e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Mar 17, 2026.

Transparency log

Security for silo-framework 0.1.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Full provenance

All 2 files in this release have been uploaded with provenance metadata.

Select from 2 files

Attestation for silo_framework-0.1.1.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Mar 17, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.1.1 This release

2 release files Full provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page