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ralph-lisa-loop

自动化的计划-实施循环,并由专家进行评审。协调器派遣子代理进行规划/实施和自我审查,Codex负责外部审查。人为控制方向。一个单一的绳长旋钮(0-5)控制中断频率。子代理架构使协调器的上下文窗口保持简洁,以便在单一会话中完成任务。适用于任何可以从结构化审查中受益的规划、开发或实施任务。

person作者: jakexiaohubgithub

ralph-lisa-loop

Preflight

Do not enter the round loop until all preflight checks pass.

Step 1: Stop hook check

Read ~/.claude/settings.json and look for a Stop hook entry pointing to this skill's scripts/stop-hook.sh.

If the hook is NOT installed, tell the user:

The ralph-lisa loop works best with the stop hook installed — it keeps the loop running automatically so you don't have to type "continue" each round. The hook is dormant when no loop session is active (it checks for a session file and exits immediately if none exists).

Want me to add it to your settings?

If the user agrees, add this entry to ~/.claude/settings.json under hooks.Stop (create the key path if it doesn't exist):

{
  "matcher": "",
  "hooks": [{
    "type": "command",
    "command": "SKILL_SCRIPTS_DIR/stop-hook.sh",
    "timeout": 10000
  }]
}

Replace SKILL_SCRIPTS_DIR with the absolute path to this skill's scripts/ directory (resolve from the skill installation location).

If the user declines the hook, proceed in Manual tier (the user will type "continue" between rounds). Note the tier in the session's first round summary.

If the hook IS already installed, proceed without mentioning it.

Step 2: Codex reviewer channel check

Probe whether the Codex MCP tools are callable (search available tools for mcp__codex__codex, or attempt a lightweight call). Don't inspect how it's configured — it could be project .mcp.json, user-wide MCP settings, or another harness entirely.

  • If mcp__codex__codex is available → record reviewer_backend: mcp and review_channel_status: mcp_ready in session, proceed.
  • If unavailable → check which codex for CLI fallback.
    • If codex CLI exists → offer to configure MCP:

      Codex MCP isn't available in this session. I can add it for you:

      1. User-level — available in all projects
      2. Project-level — scoped to this repo
      3. Skip — use codex exec CLI fallback (slower, session-based persistence)

      Which do you prefer?

      For options 1 or 2, run the appropriate command, then stop — do not enter the round loop. Tell the user to restart Claude Code and re-invoke the skill. Preflight will re-run and find MCP available.

      # User-level
      claude mcp add --scope user --transport stdio codex -- codex mcp-server
      
      # Project-level
      claude mcp add --scope project --transport stdio codex -- codex mcp-server
      

      If the user chooses "skip" (option 3), record reviewer_backend: exec and review_channel_status: exec_opt_in, proceed with the downgrade logged.

    • If no codex CLI at all → hard stop:

      The ralph-lisa loop requires Codex as reviewer. Install: npm i -g @openai/codex Then either restart (I'll offer to configure MCP) or ensure the CLI is in your PATH.

Step 3: Reasoning policy initialization

Confirm rope length and inform the user of the reasoning policy (no action needed from them):

Reasoning policy: xhigh for all rounds, with detailed reasoning summaries.

Protocol

Open @references/guide.md and follow it. Do not proceed without it.

Automated plan-implement loop with subagent workers and Codex as reviewer. The orchestrator dispatches subagents for planning/implementation and self-review, Codex for external review. Use when you want:

  • Plans stress-tested through parallel ideation then iterative convergence
  • Implementation reviewed each round with zero-finding close gate
  • Adjustable autonomy via rope-length (0 = approve everything, 5 = full auto)
  • Walk-away execution with all decisions tracked in a session file
  • Context-efficient execution that completes in a single context window

The guide contains:

  • Core protocol: orchestrator + three subagent types (planner/implementor worker, self-reviewer, Codex external reviewer)
  • Round mechanics: implement, self-review, external review, reconciliation, synthesis, gate check
  • Subagent dispatch patterns and prompt templates
  • Plan context loading rules
  • Rope-length semantics and salience scoring
  • Finding and dispute tracking with stable IDs
  • Close gate derivation and anti-gaming constraints
  • Phase transition (plan -> implement) with decisions ledger
  • Parallel ideation protocol (Round 1 independence via subagents)
  • Session file format and continuation block structure
  • Stop hook integration for loop enforcement
  • Prompt pack reference (@references/prompts.md)
  • Session template (@references/session-template.md)
  • Eval checks and failure modes