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Agent CLI skill

Add agent-friendly --json NDJSON output to Python CLI scripts, or scaffold a complete cli_utils package for a project. Use this skill when the user wants to make scripts machine-readable for AI agents, add --json flags, convert print statements to structured JSON, build a CLI helper library, create an open-source CLI-for-agents package, add structured logging, or make CLI output machine-readable. Also use when the us

$npx skills add glebis/claude-skills --skill agent-cli
View this skill on GitHubglebis/claude-skills/agent-cli/SKILL.md
Pack stars
413
Pack installs
15k
Alyn Score
59/99
Updated
7 h ago
License
MIT
– views – installs via Alyn

Install Agent CLI

Pick your agent. Every command is ready to paste.

$npx skills add glebis/claude-skills --skill agent-cli

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads agent-cli when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the agent-cli skill”. In Codex, type $agent-cli.

The skill itself

SKILL.md

FolderGitHub

Agent-Friendly CLI Builder

Convert Python CLI scripts from human-only output to agent-consumable NDJSON, or scaffold a complete cli_utils package ready for open-source distribution.

Two Modes

Mode A: Convert an existing script

When the user points at a script and says "make this agent-friendly" or "add --json":

  1. Scan the script for output points
  2. Generate cli_utils.py if the project doesn't have one
  3. Replace all output with structured helpers
  4. Verify no raw output leaks in JSON mode

Mode B: Scaffold a complete package

When the user says "create a cli_utils package" or wants an open-source library:

  1. Scaffold a full Python package with pyproject.toml, tests, license, README
  2. Include all helpers: json_log, json_error, die, log, add_json_flag, enable_json, is_json
  3. Add pytest test suite with full coverage
  4. Add MIT license (or ask user preference)

Core Architecture

The fundamental pattern: every script gets a --json flag. When active, all stdout becomes newline-delimited JSON (NDJSON). Each line is a self-contained JSON object with a standard envelope.

The NDJSON Event Envelope

Every JSON line has at minimum:

{"event": "ready", "ts": "2026-04-30T14:00:00+00:00", "pid": 1234, "port": 8765}
  • event — what happened (snake_case string)
  • ts — ISO 8601 UTC timestamp
  • Additional fields are event-specific kwargs

Why This Design

  • NDJSON over JSON arrays: processable line-by-line, one bad line doesn't break the stream, works with grep/jq, low memory for long-running processes
  • --json opt-in over default: preserves human DX, doesn't break existing scripts or habits
  • Global mode flag over per-call checks: set once at startup, every helper respects it automatically
  • die() over repeated if/else: the pattern if is_json(): json_error(); sys.exit(1) else: print(); sys.exit() appears constantly — die() collapses it to one line

The cli_utils.py Reference Implementation

When generating cli_utils.py, produce exactly this (adapt only if the project has specific needs):

"""Shared helpers for JSON CLI output."""
import json
import os
import sys
from datetime import datetime, timezone

_json_mode = False

def enable_json():
    global _json_mode
    _json_mode = True

def is_json():
    return _json_mode

def json_log(event: str, **kwargs):
    """Emit one NDJSON line to stdout."""
    obj = {"event": event, "ts": datetime.now(timezone.utc).isoformat(), **kwargs}
    print(json.dumps(obj, default=str), flush=True)

def json_error(message: str, **kwargs):
    """Emit a structured error event."""
    json_log("error", message=message, **kwargs)

def die(message: str, code: int = 1, **kwargs):
    """Print error and exit — JSON or human depending on mode."""
    if _json_mode:
        json_error(message, **kwargs)
    else:
        print(message, file=sys.stderr)
    sys.exit(code)

def add_json_flag(parser):
    """Add --json flag to an argparse parser."""
    parser.add_argument("--json", action="store_true",
                        help="NDJSON output for agent consumption")

def log(message: str, **json_kwargs):
    """Print human message normally, or emit JSON event if --json is active."""
    if _json_mode:
        json_log(json_kwargs.pop("event", "info"), message=message, **json_kwargs)
    else:
        print(message)

def json_ready(**kwargs):
    """Emit the readiness signal — only in JSON mode. Call early in daemon startup."""
    if _json_mode:
        json_log("ready", pid=os.getpid(), **kwargs)

Converting a Script — Step by Step

Step 1: Scan for output points

Search the target script for all places that produce output or exit:

grep -n 'print(\|sys\.exit\|exit(\|input(\|os\.system.*say' TARGET.py

Categorize each hit:

  • Informational print → replace with log(message, event="descriptive_name")
  • Error + exit → replace with die(message)
  • Status line with \r → replace with if is_json(): json_log("status", ...) else: print("\r...", end="", flush=True)
  • Interactive input() → guard with if not is_json(): or add --no-interactive flag
  • Side effects (say, osascript, notifications) → guard with if not is_json():
  • Import-time errors (before argparse runs) → use sys.exit("message") (writes to stderr)

Step 2: Add the import and flag

At the top of the script, after existing imports:

from cli_utils import add_json_flag, enable_json, is_json, json_log, log, die

In the if __name__ == "__main__" block, add to argparse:

add_json_flag(parser)
args = parser.parse_args()
if args.json:
    enable_json()

Step 3: Replace each output point

Apply the categorization from Step 1. Key patterns:

Simple informational:

# Before
print(f"Connected to {device}")

# After
log(f"Connected to {device}", event="connected", device=device)

Error + exit:

# Before
print("Device not found")
sys.exit(1)

# After
die("Device not found")

Daemon readiness (first output after initialization):

# Before
print(f"Server running on port {port}")

# After — json_ready() only emits in JSON mode, so always call it + human fallback
json_ready(port=port)
log(f"Server running on port {port}", event="ready", port=port)

Status lines (\r overwrite):

# Before
print(f"\r  HR {hr} RMSSD {rmssd:.1f}", end="", flush=True)

# After
if is_json():
    json_log("status", hr=hr, rmssd=rmssd)
else:
    print(f"\r  HR {hr} RMSSD {rmssd:.1f}", end="", flush=True)

Human-only output (banners, usage examples):

if not is_json():
    print("Usage: send {\"type\": \"join\", \"name\": \"Alice\"}")

Step 4: Verify

  1. Run python script.py --help — confirm --json flag appears
  2. Run python script.py --json — confirm first line is valid JSON
  3. Grep for remaining raw print( calls — ensure each is guarded or intentional

Event Name Conventions

Use snake_case, be descriptive, keep them grep-friendly:

Category Events
Lifecycle ready, shutdown, connected, disconnected
Data hr, status, metric, heartbeat
Errors error, retry
Actions recording_started, recording_stopped, preset_change
Progress scanning, connecting, downloading, importing

Scaffolding an Open-Source Package

When the user wants a distributable package, scaffold this structure:

cli-utils-agent/
├── pyproject.toml
├── LICENSE                  # MIT by default, ask user
├── README.md
├── src/
│   └── cli_utils_agent/
│       ├── __init__.py      # re-exports all public API
│       └── core.py          # the implementation
├── tests/
│   ├── __init__.py
│   ├── test_json_log.py
│   ├── test_die.py
│   ├── test_log.py
│   └── test_add_json_flag.py
└── .github/
    └── workflows/
        └── test.yml         # CI with pytest

__init__.py — re-export public API

# src/cli_utils_agent/__init__.py
from .core import (
    enable_json, is_json, json_log, json_error, die,
    add_json_flag, log, json_ready,
)

__all__ = [
    "enable_json", "is_json", "json_log", "json_error", "die",
    "add_json_flag", "log", "json_ready",
]

README.md template

Generate a README with: project name, one-line description, install instructions (pip install cli-utils-agent), quick usage example showing add_json_flag + enable_json + log(), API reference table listing all exports with one-line descriptions, and a link to the research background.

pyproject.toml template

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "cli-utils-agent"
version = "0.1.0"
description = "Add agent-friendly --json NDJSON output to any Python CLI"
readme = "README.md"
license = "MIT"
requires-python = ">=3.10"
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Developers",
    "License :: OSI Approved :: MIT License",
    "Programming Language :: Python :: 3",
    "Topic :: Software Development :: Libraries",
]

[project.urls]
Homepage = "https://github.com/USER/cli-utils-agent"

[tool.hatch.build.targets.wheel]
packages = ["src/cli_utils_agent"]

Test suite

Use capsys for stdout capture, pytest.raises(SystemExit) for die(). Example:

# tests/test_json_log.py
import json
from cli_utils_agent import json_log, enable_json, is_json

def test_json_log_writes_ndjson(capsys):
    json_log("ready", port=8765, pid=42)
    line = capsys.readouterr().out.strip()
    obj = json.loads(line)
    assert obj["event"] == "ready"
    assert obj["port"] == 8765
    assert "ts" in obj

# tests/test_die.py
import json
import pytest
from cli_utils_agent import die, enable_json
from cli_utils_agent import core as _core

def test_die_human_mode(capsys):
    _core._json_mode = False
    with pytest.raises(SystemExit) as exc:
        die("something broke")
    assert exc.value.code == 1
    assert "something broke" in capsys.readouterr().err

def test_die_json_mode(capsys):
    _core._json_mode = True
    try:
        with pytest.raises(SystemExit):
            die("something broke", code=10)
        obj = json.loads(capsys.readouterr().out.strip())
        assert obj["event"] == "error"
        assert obj["message"] == "something broke"
    finally:
        _core._json_mode = False

Cover: json_log, json_error, die, log, add_json_flag, enable_json/is_json, json_ready.

GitHub Actions CI

# .github/workflows/test.yml
name: Tests
on: [push, pull_request]
jobs:
  test:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: ["3.10", "3.11", "3.12", "3.13"]
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: ${{ matrix.python-version }}
      - run: pip install -e ".[dev]"
      - run: pytest -v

Add dev dependencies to pyproject.toml:

[project.optional-dependencies]
dev = ["pytest>=8.0"]

Checklist — Run Before Declaring Done

After converting a script or creating a package:

  • --help shows --json flag
  • Running with --json produces valid NDJSON (every line is parseable JSON)
  • First JSON line from daemons has "event": "ready"
  • Error paths emit "event": "error" with non-zero exit code
  • No raw print() can fire when --json is active
  • Import-time errors (missing deps) use sys.exit("message") not print()
  • Interactive prompts are guarded
  • Side effects (voice, notifications) are guarded
  • Human output is preserved when --json is NOT passed
  • Unhandled exceptions don't leak tracebacks to stdout in JSON mode (wrap main in try/except, emit json_error)
  • Tests pass (if package mode)
  • Package builds cleanly: python -m build (if package mode)
  • Install in clean venv and import works (if package mode)

Further Reading

Read references/best-practices.md when you need:

  • Heartbeat patterns for liveness detection (section 2.4)
  • Exit code conventions and string error codes (section 2.3)
  • Schema introspection with --schema (section 2.5)
  • CLI vs MCP decision matrix (section 2.7)
  • Token efficiency tips for agent consumption (section 5)

Tips for Agent CLI

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • It bundles reference files. The agent reads them only when needed, so they cost no context until then.
  • • It is part of a pack with 30 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Agent CLI

What does the Agent CLI skill do?

Add agent-friendly --json NDJSON output to Python CLI scripts, or scaffold a complete cli_utils package for a project. Use this skill when the user wants to make scripts machine-readable for AI agents, add --json flags, convert print statements to structured JSON, build a CLI helper library, create an open-source CLI-for-agents package, add structured logging, or make CLI output machine-readable. Also use when the us

How do I install Agent CLI?

Run "npx skills add glebis/claude-skills --skill agent-cli" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Agent CLI work in Cursor and Codex?

Yes. Agent CLI uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Agent CLI free?

Agent CLI is open source on GitHub under the MIT license. It is free to install; check the license before commercial use.

Who made Agent CLI?

Agent CLI is published by glebis in the glebis/claude-skills repository, together with 29 other skills.

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