Prompt Studio v1.0 is live on PyPI · pip install promptstudio-ai
/LEAN [X 08.4, Y 12.6]

The persona layer your agent already speaks.

One SKILL.md. Filtered per intensity by get_lean_instructions(mode) and injected in the system slot by per-provider adapters with Anthropic prompt-cache markers. Cuts LLM output size, cost, and latency · measured, not implied.

[X 08.4, Y 12.6]
/L.01 One source of truth

skills/lean/SKILL.md · read once, shipped everywhere

The plugin, MCP server, benchmark arms, and FastAPI adapters all read the same file. Bump it once · everything downstream picks it up. The system slot is marked cache_control: ephemeral, so the persona charges once per Anthropic prompt-cache TTL, not per turn.

from app.services.formats import build_messages

msgs = build_messages(
  text="Write a Python function that validates emails.",
  model_id="claude-3-5",
  intensity="full",   # "lite" | "full" | "ultra"
)
# msgs[0] → system slot with LEAN + cache_control: ephemeral
# msgs[1] → user turn
/L.02 Intensity

Three payloads, one file.

lite

Minimum payload · small models, tight context, cost-sensitive calls.

full

Default · production balance of guidance and payload.

ultra

Maximum guidance · long agentic sessions with over-build risk.

/L.03 Hosts

Ships across every major agent host.

Claude Code
Plugin · /plugin install prompt-studio@prompt-studio
Codex
Plugin · codex plugin add prompt-studio@prompt-studio
GitHub Copilot CLI
Plugin · copilot plugin install prompt-studio@prompt-studio
Devin CLI
Plugin · devin plugins install utk2103/Prompt-Studio
Qoder
Rules · .qoder/rules + hooks/qoder-hooks.json
Cursor / Windsurf / Cline / Kiro / Zed
Rules file drop into host rules directory
JetBrains / VS Code Copilot Chat / Amp / Jules / CodeWhale / Antigravity
AGENTS.md at repo root
MCP server →Install