agentpk 0.1.1

Package AI agents into portable .agent files

agentpk

The open source CLI for packaging AI agents.

pip install agentpk

Quickstart

agent init my-agent
# edit my-agent/manifest.yaml
agent pack my-agent/

That's it. You now have a portable my-agent-0.1.0.agent file you can share, deploy, or register.

# Run it
agent run my-agent-0.1.0.agent

# Sign it
agent keygen --out my-key.pem
agent sign my-agent-0.1.0.agent --key my-key.pem

What is the .agent format?

An .agent file is a ZIP archive containing your agent source code, a manifest.yaml that describes what your agent does and what it needs, and a checksums.sha256 file that verifies nothing was tampered with. Any tool that can read ZIP files can open it.

The manifest is the important part. It tells runtimes how to start your agent and tells registries how to list it. One file, two audiences.

Naming convention

Agent names must be lowercase with hyphens and digits only. They must start with a letter.

Valid	Invalid
fraud-detection	Fraud_Detection
my-agent-2	my agent
data-pipeline	data.pipeline

CLI commands

Command	Description
agent init <name>	Scaffold a new agent project
agent pack <dir>	Pack a directory into a .agent file
agent validate <target>	Validate a .agent file or project directory
agent inspect <file>	Display metadata from a .agent file
agent unpack <file>	Extract a .agent file to a directory
agent diff <old> <new>	Show differences between two .agent files
agent test	Run built-in self-tests to verify installation
agent generate [dir]	Generate a manifest.yaml from code analysis
agent list [dir]	List all .agent files in a directory
agent run <file>	Execute a packed .agent file as a subprocess
agent sign <file>	Sign a .agent file with a private key
agent verify <file>	Verify the signature on a .agent file
agent keygen	Generate an RSA key pair for signing

Listing agents

Scan a directory for .agent files and display a summary table:

agent list
agent list ./agents/
agent list ./agents/ --recursive
agent list ./agents/ --json

--recursive walks subdirectories. --json prints machine-readable JSON instead of a Rich table. Invalid .agent files are included in the listing with a warning rather than causing the command to fail.

Running agents

Execute a packed .agent file as a subprocess:

agent run my-agent-1.0.0.agent
agent run my-agent-1.0.0.agent --dry-run
agent run my-agent-1.0.0.agent --keep
agent run my-agent-1.0.0.agent --env API_KEY=abc123
agent run my-agent-1.0.0.agent -- --flag value

The runner extracts the package to a temp directory, validates it, and launches the entry point using the runtime declared in the manifest (Python, Node.js, or TypeScript). Extra arguments after -- are forwarded to the agent process.

Flag	Effect
--dry-run	Validate and extract without executing
--keep	Keep the temp directory after execution
--env KEY=VALUE	Set environment variables (repeatable)

Warning: agent run executes code from the package. Only run agents from sources you trust.

Code analysis and trust scores

agentpk can analyze agent source code and assign a trust score indicating how well the manifest matches what the code actually does.

See docs/agent_analyzer.md for the full architecture documentation.

Generating a manifest from code

If you have agent source code but no manifest.yaml, generate one:

agent generate ./my-agent
agent generate ./my-agent --level 3

The generated manifest includes # REVIEW markers on fields that could not be determined from code analysis alone (display name, author, etc.).

Packing with analysis

Add --analyze to agent pack to run code analysis and embed a trust score in the package:

agent pack my-agent/ --analyze
agent pack my-agent/ --analyze --level 3
agent pack my-agent/ --analyze --level 3 --strict

Flag	Effect
--analyze	Run code analysis before packing
--level N	Analysis depth 1-4 (default: auto)
--strict	Fail if requested level cannot be reached
--on-discrepancy warn|fail|auto	Discrepancy handling (default: warn)

Analysis levels

Level	Source	Needs	Weight
1	Structural validation	Nothing	+20 pts
2	Static AST analysis	Nothing	+30 pts
3	LLM semantic analysis	API key	+25 pts
4	Runtime sandbox	Docker	+25 pts

Skipped levels subtract points (Level 3 skip: -15, Level 4 skip: -25). The maximum score is 100 when all four levels pass with no discrepancies.

Trust score labels

Score	Label
90-100	Verified
75-89	High
60-74	Moderate
40-59	Low
0-39	Unverified

When you inspect a package, the trust score is displayed. Packages without analysis show "unverified."

Signing and verification

agentpk includes built-in cryptographic signing so recipients can verify that a .agent file was produced by a trusted party and has not been modified.

Generate a key pair

agent keygen --out my-key.pem

This creates two files:

• my-key.pem -- RSA-2048 private key (keep secret)
• my-cert.pem -- self-signed X.509 certificate (share with recipients)

Sign an agent

agent sign fraud-detection-1.0.0.agent --key my-key.pem
agent sign fraud-detection-1.0.0.agent --key my-key.pem --signer "Acme AI"

This produces a .sig file alongside the .agent file (e.g. fraud-detection-1.0.0.agent.sig). The .sig file is JSON containing the manifest hash, an RSA-PSS-SHA256 signature, and optional signer metadata.

Verify a signature

agent verify fraud-detection-1.0.0.agent --cert my-cert.pem

Verification re-computes the manifest hash, compares it to the value in the .sig file, and cryptographically verifies the signature against the certificate. If the agent or signature has been tampered with, verification fails.

Manifest structure

The manifest has two zones:

Zone 1 (open core) contains everything a runtime needs: identity fields (name, version, description), runtime configuration (language, entry point, dependencies), capabilities (tools your agent exposes), execution settings (scheduled, triggered, or on-demand), and resource requirements.

Zone 2 (_package) is generated automatically at pack time. It contains hashes, timestamps, file counts, and package size. Never edit this zone by hand.

Validation

Validate a project directory or packed .agent file against the 6-stage validation pipeline:

agent validate ./my-agent/
agent validate my-agent-1.0.0.agent
agent validate my-agent-1.0.0.agent --verbose

The --verbose flag displays a per-stage breakdown showing which stages passed, failed, or were skipped. Directories skip stages 5-6 (checksums and package integrity) since those only apply to packed files.

Verifying Your Installation

Run the built-in self-test suite to confirm agentpk is working correctly:

agent test

This generates 14 temporary agent fixtures (4 valid, 10 invalid), runs the validation pipeline against each one, and reports pass/fail results. Add --verbose for per-test detail:

agent test --verbose

Examples

Five valid examples and eleven intentionally broken examples are included in examples/. See examples/README.md for the full table.

# Pack a valid example
agent pack examples/valid/fraud-detection

# Confirm an invalid example is correctly rejected
agent pack examples/invalid/04-invalid-name

Specification

See SPEC.md for the full agent package format specification.

Development

pip install -e ".[dev]"
pytest

Dependencies: click, pyyaml, pydantic, rich, cryptography.

About

Built by Nomotic AI.

License

Code: MIT Specification (SPEC.md): CC BY 4.0