Developing With Agentsquire

Developing with agentsquire

agentsquire lets your Python package carry its own Agent Skills and install them into whatever agent harness is present (Claude Code, pi, Hermes, opencode). Your users only ever run your tool - your-cli skills install - never a second CLI.

Add agentsquire as a plain dependency, then wire the four points below. This is a checklist, not the reference: run squire guide (topics api, harnesses, integration) or read docs/api.md for full signatures and behaviour.

1. Ship skills as package data

Lay each skill out as a directory with a SKILL.md (agentskills.io format) under a skills/ resource inside your importable package:

your_pkg/
    __init__.py
    skills/
        my-skill/
            SKILL.md

The skills ride inside your wheel, so no source checkout is needed at run time. hatchling includes package data by default; setuptools needs include-package-data. This skills-as-package-data layout is what BundledPackageDataSource("your_pkg") reads from.

2. Mount the skills subcommand group

skills_command_group returns a click group with install, status, update, and uninstall subcommands, parameterized by your package name and default scope. Mount it on your root group:

from agentsquire.cli import skills_command_group

cli.add_command(skills_command_group("your_pkg", default_scope="user"))

For typer, mount onto typer.main.get_command(app). Every subcommand takes --scope user|project and --harness NAME. Choose user scope for general-purpose tools, project for repo-specific skills.

3. Expose a console entry point

Give your CLI a [project.scripts] console entry in pyproject.toml so users invoke it by name:

[project.scripts]
your-cli = "your_pkg.console:main"

4. Surface updates proactively (optional)

Call the check_stale hook at your entry point. When an installed skill has a newer shipped copy it prints one advisory line on stderr and nothing else - it never prompts, never writes stdout, never changes your exit code:

from agentsquire import BundledPackageDataSource, check_stale

def main():
    check_stale(
        BundledPackageDataSource("your_pkg"),
        prog_name="your-cli",
        update_command="your-cli skills update",
    )
    # ... rest of your entry point

Suppressed when CI or AGENTSQUIRE_NO_UPDATE_CHECK is set to any non-empty value.

5. Mark the package as skill-carrying (optional)

One pyproject line registers your package under the agentsquire.skills entry-point marker. Nothing reads it today; it is reserved for a future environment-wide listing and changes no behaviour:

[project.entry-points."agentsquire.skills"]
your_pkg = "your_pkg"

The provenance and update model

Installs are plain copies - no symlinks, no lockfile - so an installed skill survives upgrade or removal of your package. Each installed SKILL.md carries a provenance stamp in its frontmatter metadata.agentsquire map (installer, versions, source package, content hash). Staleness detection is a local hash compare: status classifies each skill as not-installed, up-to-date, update-available, or locally-modified, and update refreshes only the stale ones. User-modified installs and pre-existing symlinks are reported and skipped, never clobbered. See squire guide integration for the full model.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: TacoTakumi
• Source: TacoTakumi/AgentSquire
• License: MIT

Install and usage instructions live in the source repository linked above.