Files
microsoft-SkillOpt/pyproject.toml
Yifan Yang f9db99853b feat(plugins): ship SkillOpt-Sleep for Claude Code, Codex, and Copilot
Restructure into plugins/{claude-code,codex,copilot}/ — one engine, three thin
shells, all calling the shared plugins/run-sleep.sh -> python -m skillopt_sleep.

  - claude-code/: existing plugin moved here; runner delegates to the shared
    launcher (fixes repo-root resolution after the move).
  - codex/: ~/.codex/prompts/sleep.md custom prompt + ~/.agents/skills SKILL.md +
    install.sh + AGENTS.md hint — Codex's documented, stable extension surfaces.
  - copilot/: a stdlib-only MCP server (mcp_server.py) exposing sleep_* tools,
    plus mcp-config.example.json and a copilot-instructions snippet. Verified end
    to end (initialize -> tools/list -> tools/call returns real engine output).
  - plugins/README.md overview table; main README News + a dedicated SkillOpt-Sleep
    section; pyproject lists skillopt_sleep as a first-class package.

Decoupling emphasized throughout: open-source tool (skillopt_sleep/) with zero
dependency on the research package. 29 tests pass; all three shells resolve.

Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>
2026-06-08 14:31:52 +00:00

78 lines
2.2 KiB
TOML

[build-system]
requires = ["setuptools>=68.0", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "skillopt"
version = "0.1.0"
description = "SkillOpt: Agentic Skill Optimization via Reflective Training Loops"
readme = "README.md"
license = {text = "MIT"}
requires-python = ">=3.10"
authors = [
{name = "SkillOpt Team"},
]
keywords = ["agent", "prompt-optimization", "skill-learning", "LLM", "agentic"]
classifiers = [
"Development Status :: 3 - Alpha",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
]
dependencies = [
"openai>=1.30.0",
"pyyaml>=6.0",
"numpy>=1.24.0",
"openpyxl>=3.1.0",
"azure-identity>=1.15.0",
"azure-core>=1.30.0",
"httpx>=0.27.0",
]
[project.optional-dependencies]
# Benchmark-specific dependencies
alfworld = ["alfworld>=0.4.0", "gymnasium>=0.29.0"]
# Claude model backend
claude = ["claude-agent-sdk>=0.1.0"]
# Qwen local model backend (via vLLM)
qwen = ["vllm>=0.4.0"]
# Documentation site
docs = ["mkdocs-material>=9.5.0", "mkdocstrings[python]>=0.24.0"]
# WebUI dashboard
webui = ["gradio>=4.0.0"]
# Development tools
dev = ["ruff>=0.4.0", "pytest>=8.0.0"]
# All optional dependencies (except docs/dev/webui)
all = [
"alfworld>=0.4.0",
"gymnasium>=0.29.0",
"claude-agent-sdk>=0.1.0",
]
[project.scripts]
skillopt-train = "scripts.train:main"
skillopt-eval = "scripts.eval_only:main"
[project.urls]
Homepage = "https://github.com/microsoft/SkillOpt"
Documentation = "https://microsoft.github.io/SkillOpt"
Repository = "https://github.com/microsoft/SkillOpt"
Issues = "https://github.com/microsoft/SkillOpt/issues"
[tool.setuptools.packages.find]
# skillopt* = the research package; skillopt_sleep = the open-source Sleep tool
# (decoupled, zero dependency on the research code).
include = ["skillopt", "skillopt.*", "skillopt_sleep", "skillopt_sleep.*", "scripts*"]
[tool.ruff]
line-length = 120
target-version = "py310"
[tool.ruff.lint]
select = ["E", "F", "I", "W"]
ignore = ["E501"]