Delegate independent tasks to specialized agents working concurrently with isolated context.
List Skills
list_skills
Imported skill list_skills from openai
SKILL.md
Full skill instructions
#!/usr/bin/env python3 """List skills from a GitHub repo path."""
from future import annotations
import argparse import json import os import sys import urllib.error
from github_utils import github_api_contents_url, github_request
DEFAULT_REPO = "openai/skills" DEFAULT_PATH = "skills/.curated" DEFAULT_REF = "main"
class ListError(Exception): pass
class Args(argparse.Namespace): repo: str path: str ref: str format: str
def _request(url: str) -> bytes: return github_request(url, "codex-skill-list")
def _codex_home() -> str: return os.environ.get("CODEX_HOME", os.path.expanduser("~/.codex"))
def _installed_skills() -> set[str]: root = os.path.join(_codex_home(), "skills") if not os.path.isdir(root): return set() entries = set() for name in os.listdir(root): path = os.path.join(root, name) if os.path.isdir(path): entries.add(name) return entries
def _list_skills(repo: str, path: str, ref: str) -> list[str]: api_url = github_api_contents_url(repo, path, ref) try: payload = _request(api_url) except urllib.error.HTTPError as exc: if exc.code == 404: raise ListError( "Skills path not found: " f"https://github.com/{repo}/tree/{ref}/{path}" ) from exc raise ListError(f"Failed to fetch skills: HTTP {exc.code}") from exc data = json.loads(payload.decode("utf-8")) if not isinstance(data, list): raise ListError("Unexpected skills listing response.") skills = [item["name"] for item in data if item.get("type") == "dir"] return sorted(skills)
def _parse_args(argv: list[str]) -> Args: parser = argparse.ArgumentParser(description="List skills.") parser.add_argument("--repo", default=DEFAULT_REPO) parser.add_argument( "--path", default=DEFAULT_PATH, help="Repo path to list (default: skills/.curated)", ) parser.add_argument("--ref", default=DEFAULT_REF) parser.add_argument( "--format", choices=["text", "json"], default="text", help="Output format", ) return parser.parse_args(argv, namespace=Args())
def main(argv: list[str]) -> int: args = _parse_args(argv) try: skills = _list_skills(args.repo, args.path, args.ref) installed = _installed_skills() if args.format == "json": payload = [ {"name": name, "installed": name in installed} for name in skills ] print(json.dumps(payload)) else: for idx, name in enumerate(skills, start=1): suffix = " (already installed)" if name in installed else "" print(f"{idx}. {name}{suffix}") return 0 except ListError as exc: print(f"Error: {exc}", file=sys.stderr) return 1
if name == "main": raise SystemExit(main(sys.argv[1:]))
More Other skills
brand-guidelines
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
theme-factory
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
internal-comms
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Fundamental design principles for writing maintainable, testable Python code.
responsive-design
Modern responsive layouts using container queries, fluid typography, CSS Grid, and mobile-first strategies.
Generate Playwright tests from scenarios using interactive browser exploration and validation.
Automated website exploration and test case generation using Playwright.
Modern React state management with Redux Toolkit, Zustand, Jotai, and React Query for every state category.
gdpr-data-handling
GDPR-compliant data handling with consent management, data subject rights, and privacy controls.
Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.
refactor-plan
Detailed multi-file refactor planning with safety checks and rollback guidance.
