Metadata-Version: 2.5
Name: toolfuncs
Version: 0.12.1
Summary: Executable typed Python function tools invoked by path or discovered through PATH
Project-URL: Repository, https://github.com/nimashoghi/toolfuncs
Project-URL: Issues, https://github.com/nimashoghi/toolfuncs/issues
Author-email: Nima Shoghi <nima@boltz.bio>
Requires-Python: >=3.11
Requires-Dist: cyclopts<5,>=4.25.1
Requires-Dist: packaging>=24
Requires-Dist: pydantic-core<3,>=2
Requires-Dist: pydantic<3,>=2
Requires-Dist: uv-launch<0.3,>=0.2.1
Provides-Extra: hooks
Requires-Dist: typed-agent-hooks; extra == 'hooks'
Description-Content-Type: text/markdown

# toolfuncs

`toolfuncs` turns typed Python functions into tools that have matching Python and command-line interfaces.

A toolfunc exposes typed functions through one module-level `App`. It can be an executable Python script or an explicitly opted-in installed package console script. Its lowercase kebab-case command name determines the Python facade name by replacing hyphens with underscores. `PATH` controls discovery and lookup in both cases; ordinary installed commands do not become toolfuncs automatically.

## Package a tool

Use ordinary project metadata with matching console-script and toolfuncs entry points:

```toml
[project]
name = "agent-apps"
version = "0.1.0"
dependencies = ["toolfuncs"]

[project.scripts]
agent-apps = "agent_apps.tools:app"

[project.entry-points.toolfuncs]
agent-apps = "agent_apps.tools:app"
```

Define the interface once in `agent_apps/tools.py`:

```python
"""Manage agent application conversations."""

import toolfuncs.sdk as toolsdk

app = toolsdk.App()


@app.command
def describe(conversation: str) -> dict[str, str]:
    """Describe one conversation.

    Parameters
    ----------
    conversation:
        Conversation identifier to inspect.
    """
    return {"conversation": conversation}
```

Install with `uv-launch install agent-apps "agent-apps @ file:///absolute/path/to/project"` for managed launches, or with a normal package installer for an unmanaged command. The installer generates the console script; no separate handwritten executable, self-dependent PEP 723 script, custom backend, or registration command is needed. `agent-apps describe example` calls the same decorated function exposed as `toolfuncs.agent_apps.describe("example")`. Direct Python lookup returns the real `agent_apps.tools` module and native objects/exceptions.

Discovery reads the installed distribution's entry points, file ownership, and module docstring without importing or executing the target or preparing dependencies. It validates that the effective PATH launcher actually calls the declared `module:app`. Standard Python launchers, symlinks, installer-generated `/bin/sh` wrappers for long interpreter paths, and uv-launch managed commands are supported. The package must include inspectable Python source in its installation; arbitrary shell launchers and editable import-hook layouts are not inferred. The first docstring line is the static description.

Direct Python loading installs the owning distribution into the caller's interpreter if needed, using its recorded exact Git origin, other direct origin, or published name/version. It then imports the actual module. This preserves native Python semantics rather than opening an RPC proxy into the tool environment. Use a suitable interpreter when tools have incompatible dependency requirements. `toolfuncs doctor /path/to/agent-apps` validates the installed module's registered commands and generated help. `import_path` retains its existing local-script contract and does not import package console wrappers.

## Write a toolfunc

Create an extensionless file named `weather-report`:

```python
#!/usr/bin/env toolfuncs
# /// script
# requires-python = ">=3.11"
# dependencies = ["weather-client"]
# [tool.toolfuncs]
# description = "Read current weather conditions."
# cli_name = "weather-report"
# python_name = "weather_report"
# ///

import toolfuncs.sdk as toolsdk
import weather_client

app = toolsdk.App()


@app.command
def current(city: str) -> dict[str, object]:
    """Read current conditions for one city.

    Parameters
    ----------
    city:
        City whose current conditions should be read.
    """

    return weather_client.current(city)
```

Make it executable:

```console
chmod +x weather-report
```

No registration operation is required. Move it to an existing `PATH` directory only when it should be globally discoverable:

```console
mv weather-report ~/.local/bin/
```

## Call it

A known source can be run explicitly without adding it to `PATH`:

```console
$ toolfuncs ./weather-report current London
{"city": "London", "temperature": 18}
```

When the source is on `PATH`, its filename is also the CLI:

```console
$ weather-report current London
{"city": "London", "temperature": 18}
```

A known source is importable by path:

```python
import toolfuncs as tools

weather_report = tools.import_path("./weather-report")
conditions = weather_report.current("London")
```

When the source is on `PATH`, the same file is also dynamically importable by name in a Python process with that `PATH`:

```python
import toolfuncs as tools

conditions = tools.weather_report.current("London")
```

`import_path()` also works for an ordinary local Python script whose path is already known:

```python
import toolfuncs as tools

module = tools.import_path("scripts/prepare_data.py")
```

It accepts one ordinary `.py` file or extensionless script and derives the module name from its filename. An extensionless lowercase kebab-case filename is mapped to its snake-case Python name. It does not require a shebang, executable bit,
`[tool.toolfuncs]` metadata, or `App`, and it does not import packages, projects,
distributions, or URLs. When an optional PEP 723 block exists, the default
installer installs all declared requirements together into the running Python
environment before import. A caller can replace that behavior with one callable
that accepts `list[str]` and returns `None`:

```python
module = tools.import_path(
    "scripts/prepare_data.py",
    dependency_installer=my_installer,
)
```

Python dependency preparation uses uv-launch: it reuses satisfying installed distributions and adds missing packages to the current interpreter. Conflicts fail before installation instead of replacing existing packages. Background resolution refresh never mutates the active interpreter. Repeated imports retain their actual module objects; a new kernel does not itself reset an existing virtual environment.

Direct Python calls return ordinary Python objects and raise the original exceptions. Dynamic tool attributes and `toolfuncs.import_path()` prepare declared requirements in the running Python environment before import. CLI calls use Cyclopts to parse annotated values. Interactive terminals receive Rich help, errors, and Python-object result rendering; pipes and other non-terminal destinations receive plain help and errors plus strict JSON results through `pydantic-core`.

Set `TOOLFUNCS_OUTPUT=terminal` or `TOOLFUNCS_OUTPUT=machine` before invoking a tool to force either presentation. The default `auto` mode decides independently for stdout and stderr, so redirecting a result preserves machine-readable stdout without changing an attached terminal's error presentation. Explicit Cyclopts `help_formatter`, `error_formatter`, and `result_action` settings remain authoritative for tools with specialized output protocols. Help and version are framework control operations, so their internal return values bypass the command result action; a registered command that returns `None` remains an ordinary result and renders as `None` or `null` according to the selected mode.

Function commands registered with `@app.command` inherit these output policies from their parent app. Set a policy on `@app.command(...)` to override it for that command. Registering an existing `App` preserves that app's own configuration.

## Source contract

A toolfunc source must:

1. be one executable file;
2. have an extensionless lowercase ASCII kebab-case filename;
3. start with one of the two exact toolfuncs shebangs described below;
4. contain exactly one PEP 723 `script` block with `dependencies`, a one-line description, and required `cli_name` and `python_name` documentation that exactly matches the filename-derived identities;
5. define a module-level `app = toolsdk.App()` after `import toolfuncs.sdk as toolsdk`;
6. give the module and every registered operation a docstring, annotate every operation parameter and return value, and provide effective Cyclopts help for every visible CLI argument;
7. register each CLI-callable function explicitly with `@app.command`.

The PEP 723 dependency list contains the packages needed in addition to the running toolfuncs environment. Listing `toolfuncs` itself is accepted but normally redundant because the shebang has already started the toolfuncs runtime before dependencies are prepared.

Descriptions are static by default. A tool whose available domain surface changes at runtime may opt into a last-known catalog description with `dynamic = true`:

```toml
[tool.toolfuncs]
description = "Use connected services."
dynamic = true
cli_name = "connected-services"
python_name = "connected_services"
```

After refreshing its own state, the tool publishes one current line without changing its source:

```python
toolsdk.publish_description(
    "connected-services",
    "Use connected services: Gmail, Google Drive, and Slack.",
)
```

Toolfuncs stores the line at `${XDG_STATE_HOME:-~/.local/state}/toolfuncs/descriptions/connected-services`. Missing or invalid state uses the required static description. The CLI and Python identities always remain static.

Git requirements may use full commits, branches, tags, abbreviated hashes, or the default branch. uv-launch pins each cached resolution to exact commits and checks for updates in the background. The ordinary `#!/usr/bin/env toolfuncs` shebang is sufficient. The older `--allow-floating-vcs` shebang is accepted but no longer changes policy. Adjacent `uv lock --script` files are not consumed; uv-launch owns the cached resolutions.


Only functions registered on `app` become CLI commands. Imported functions and `__all__` do not define the command surface. Function command and option spelling follows Cyclopts' Python-to-kebab-case projection.

No `if __name__ == "__main__":` block is required. The operating system passes the source path to the shebang interpreter, and toolfuncs imports the source under its declared Python name before invoking its module-level app. Consequently, `weather-report ...` is the supported CLI while `python weather-report ...` merely defines the module and exits, or fails if its dependencies are not already installed.

## Package-backed implementations

A toolfunc remains one script even when most of its implementation lives in a package:

```python
#!/usr/bin/env toolfuncs
# /// script
# requires-python = ">=3.11"
# dependencies = ["my-large-package"]
# [tool.toolfuncs]
# description = "Run the package's agent operation."
# cli_name = "package-operation"
# python_name = "package_operation"
# ///

from my_large_package.agent_tool import app, perform_operation
```

The imported `app` and functions are the original Python objects. Toolfuncs does not inspect the package's project layout, metadata, or import structure.

## Discovery and precedence

Toolfuncs reads the current process's `PATH` from left to right. It considers only executable files and symlinks, reads their first line, and parses PEP 723 metadata only when either exact toolfuncs shebang matches.

The first executable filename claims a command name even when it is not a toolfunc. Therefore an ordinary executable earlier on `PATH` hides a same-named toolfunc later on `PATH`, matching what the shell actually executes. Repeated directories are scanned once, inaccessible directories are skipped, and discovered records are sorted by CLI name.

`toolfuncs list` returns one JSON object with `tools` and `invalid_tools`. Valid records contain `cli`, `python`, `path`, and the effective `description`; `python` is the complete dynamic facade name, such as `toolfuncs.weather_report`. For `dynamic = true`, discovery reads the optional one-line state file and otherwise uses the static description. An opted-in but invalid tool is reported with its path and validation error without hiding unrelated valid tools; the command also prints a concise warning to stderr and exits successfully. Listing never imports a tool, prepares its dependencies, executes its source, or accesses the network.

## Validate a tool while authoring

Run the doctor against one explicit source before installing or committing it:

```console
toolfuncs doctor ./weather-report
```

The doctor validates the static source contract, prepares the declared dependencies, loads the source, and inspects the actual Cyclopts command graph. It requires a module docstring, at least one registered operation, a docstring and complete annotations for every operation, effective help text for every visible parsed CLI argument, and successful root and command help generation. Aliases are inspected once through their underlying command.

The result is always one strict-JSON tagged union. A valid source exits zero:

```json
{"status": "success", "path": "/path/to/weather-report", "commands": ["current"]}
```

Expected authoring failures return `status: "error"`, list every independently detectable operation error, and exit nonzero without using an exception as the result:

```json
{"status": "error", "path": "/path/to/weather-report", "errors": ["current: CLI argument '--city' must have help text"]}
```

Loading is intentional: the registered command graph and Cyclopts' effective parameter help can be constructed dynamically and should not be approximated with a second source parser. The CLI doctor prepares an isolated uv-launch runtime; calling the Python doctor directly uses the current interpreter.

## Install the runtime

```console
uvx --from "toolfuncs>=0.12" toolfuncs setup
```

Setup installs uv-launch in a stable uv tool environment, prepares managed `toolfuncs` and `toolfuncs-agent-hook` commands, and writes small forwarding wrappers at `~/.local/bin/toolfuncs` and `~/.agents/hooks/toolfuncs/hook`. These wrappers no longer invoke uvx on each call. The destination must already be on PATH; setup is idempotent, refuses to overwrite unmanaged commands, and does not modify shell profiles.

Both shebang invocation and `toolfuncs SOURCE` delegate requirements to uv-launch before executing the source in an immutable environment. First use waits for installation. Warm calls reuse an existing environment and check for dependency updates in the background. Source edits run immediately; changed requirements or interpreter constraints select or prepare a matching environment before execution. Failed background updates leave the last working environment available. `toolfuncs doctor SOURCE` uses the same isolated preparation.

The managed hook uses the `toolfuncs[hooks]` environment and is registered at user scope for Codex and Claude Code through `typed-agent-hooks`. Running setup again reconciles those registrations, so the managed launcher remains the configured executable even when provider configuration changes.

Setup does not discover, copy, register, link, synchronize, or remove tools. There is no dedicated tools directory, registry, manifest, generated shim, project scope, user scope, or sync command.

## Management commands

```console
toolfuncs SOURCE [ARGS...]
toolfuncs doctor SOURCE
toolfuncs list
toolfuncs setup [--bin-dir DIRECTORY]
```

`toolfuncs SOURCE [ARGS...]` runs a known source directly. This is the explicit-source interface, not a name dispatcher: `toolfuncs weather-report` resolves `weather-report` as a source path rather than searching `PATH` for that tool name. A toolfunc on `PATH` can instead be invoked directly by its own filename.

## Agent integration

The installed hook runs at initial session start and at the session-start event emitted after compaction. It discovers the effective tools directly from that harness process's `PATH`, then adds a compact catalog such as:

```text
Available toolfuncs:
- `weather_report`: Read current weather conditions.
  CLI: `weather-report --help`
  Python: `import toolfuncs as tools; help(tools.weather_report)`
```

The hook reads executable headers and PEP 723 metadata, plus the optional one-line state file for tools declaring `dynamic = true`. It advertises valid tools and lists invalid tool paths and errors separately; one invalid tool does not suppress the others. It does not import tools, resolve their dependencies, execute them, or access the network. The hook itself is harness infrastructure, not a toolfunc, and therefore does not carry the toolfuncs shebang or appear in the catalog.

## Development

```console
uv sync
uv run pytest
uv run ruff format --check .
uv run ruff check .
uv run basedpyright
```

The exact guarantees and non-goals are recorded in [the contract](docs/contract.md).

## Releasing

The GitHub Release is the release control point. Set `[project].version`, merge and push that commit, then publish a GitHub Release whose tag is `v<version>`. The self-hosted release workflow verifies that the tag and package version match, builds the wheel and source distribution, and publishes them to PyPI through Trusted Publishing.

## Prepared source installations

For a toolfunc delivered together with adjacent files, use `uv-launch install-source NAME REPOSITORY SOURCE`. The launcher resolves the PEP 723 dependencies and validates the tool before selecting a generation. PATH discovery and the Python facade recognize the managed source without executing its shell wrapper.

`toolfuncs run-prepared SOURCE ARGS...` executes in the caller's already selected environment. `toolfuncs doctor --prepared SOURCE` validates that same boundary. These commands are for environment managers and integration tests; ordinary local development can continue to use `toolfuncs SOURCE ARGS...`, which prepares declared dependencies when necessary.
