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Improvement Orchestrator

作者 _silhouette · GitHub ↗ · v1.1.1 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install improvement-orchestrator
功能描述
当需要一键跑完「生成→评分→评估→执行→门禁」全流程、失败后自动重试、或批量改进多个 skill 时使用。不用于单独评估 skill 质量(用 improvement-learner)或手动打分(用 improvement-discriminator)。
使用说明 (SKILL.md)

Improvement Orchestrator

Coordinates the full improvement pipeline: Generator → Discriminator → Evaluator → Executor → Gate.

When to Use

  • Run a full improvement cycle on one or more skills
  • Coordinate the 5-stage pipeline end-to-end (with optional evaluator)
  • Retry failed improvements with trace-aware feedback (Ralph Wiggum loop)

When NOT to Use

  • 只想检查 skill 质量评分 → use improvement-learner
  • 只想手动给候选打分 → use improvement-discriminator
  • 只想改一个文件 → use improvement-executor
  • 只想查基准数据 → use benchmark-store

Pipeline

propose → discriminate → evaluate* → execute → gate
         ↻ Ralph Wiggum: fail → inject trace → retry (max 3)
         * evaluate is optional — skipped if no task_suite.yaml exists

\x3Cexample> 正确用法: 对一个 skill 运行全流程改进 $ python3 scripts/orchestrate.py --target /path/to/skill --state-root ./state → 自动完成: 生成候选 → 多人盲审 → 任务评估 → 执行变更 → 6层门禁 → 失败时自动注入 trace 重试(最多 3 次) \x3C/example>

\x3Canti-example> 错误用法: 只想看评分却用了 orchestrator $ python3 scripts/orchestrate.py --target /path/to/skill # 会执行变更! → 应该用: python3 improvement-learner/scripts/self_improve.py --skill-path /path/to/skill --max-iterations 1 \x3C/anti-example>

CLI

python3 scripts/orchestrate.py \
  --target /path/to/skill \
  --state-root /path/to/state \
  --max-retries 3 \
  --auto

Output Artifacts

Request Deliverable
Full pipeline JSON with all stage outputs, final scores, execution trace
Retry cycle Updated candidates with injected failure traces

Related Skills

  • improvement-generator: Produces candidate proposals (stage 1)
  • improvement-discriminator: Multi-reviewer panel scoring (stage 2)
  • improvement-evaluator: Task suite execution validation (stage 3, optional)
  • improvement-executor: Applies changes with backup/rollback (stage 4)
  • improvement-gate: 6-layer quality gate (stage 5)
  • benchmark-store: Frozen benchmarks and Pareto front data

References

安全使用建议
This orchestrator is coherent with its documentation: it runs local improvement scripts and may modify files under the --target path, but only supports conservative, low-risk changes (Markdown appends) in this first version and creates backups and audit artifacts. Before installing or running: (1) point --target at a safe test copy (not infra or gateway configs), (2) inspect the generated state/backups directory after a dry run, (3) prefer using --state-root in an isolated temp directory, and (4) verify the full repo layout (other improvement-* scripts and lib.*) exists in the environment so the orchestrator calls the intended local code. If you want stronger safety, run it without --auto first to inspect each step's outputs or run in a sandbox repository.
功能分析
Type: OpenClaw Skill Name: improvement-orchestrator Version: 1.1.1 The 'improvement-orchestrator' skill bundle is a coordination tool designed to manage a multi-stage AI skill improvement pipeline (Propose, Discriminate, Evaluate, Execute, and Gate). The primary logic in 'scripts/orchestrate.py' uses subprocess calls to execute local Python scripts corresponding to each stage, managing state transitions and implementing a retry loop for failed improvements. The bundle includes extensive documentation and unit tests ('tests/test_orchestrate.py') that demonstrate a well-structured and transparent design. Security-wise, the 'references/guardrails.md' file explicitly defines safety boundaries, limiting automated changes to low-risk documentation files and requiring human intervention for higher-risk modifications. No evidence of malicious intent, data exfiltration, or unauthorized execution was found.
能力评估
Purpose & Capability
Name/description match the implementation: the skill coordinates proposer→critic→evaluator→executor→gate. It requires no unusual environment variables or external credentials. The code expects a repo-style layout (other improvement-* skills and lib.* helpers) which is consistent with an orchestrator that dispatches to sibling scripts.
Instruction Scope
SKILL.md and scripts explicitly instruct the agent to run local Python scripts that will read and write filesystem artifacts (candidate/ranking/execution/receipt/state files) and may apply low-risk changes (append_markdown_section) to target skills. This is within scope, but the runtime will modify files under the provided target path and create backups/traces — users should ensure the target path is correct and not a protected or infra-critical path.
Install Mechanism
There is no install spec (instruction-only plus local scripts). Nothing is downloaded or written by an installer. Risk from install-time network downloads is not present.
Credentials
No environment variables, credentials, or external tokens are requested. The orchestrator operates on local file paths and local sibling scripts; it does not request unrelated secrets or remote API keys.
Persistence & Privilege
The skill is user-invocable and can be invoked autonomously by the agent (normal default). It does create persistent local artifacts (state, backups, traces) and modifies target files when the executor accepts a candidate. It does not set always:true. Because it can apply changes to local files, run it with appropriate target paths and review produced artifacts/backups when used.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install improvement-orchestrator
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /improvement-orchestrator 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.1
v2.0: 9-dim evaluation, category modifiers, per-dim Pareto tolerances, enriched docs
v1.1.0
v1.1.0: Fix 4 critical pipeline bugs (Ralph Wiggum/Autoloop/Evaluator verdict), scoring overhaul (base 4->2, LLM weight 50%, semantic relevance), generator LLM-first, learner/gate/executor fixes
v1.0.0
- Initial release of improvement-orchestrator. - Enables automated end-to-end improvement workflow for one or multiple skills, covering generation, scoring, quality gating, execution, and learning. - Supports automatic retry with failure trace injection (up to 3 times) for robust improvement cycles. - Not intended for single-stage evaluation or manual scoring—use specialized tools for those tasks. - Comprehensive CLI, clear usage guidance, and related skills referenced for modular workflows.
元数据
Slug improvement-orchestrator
版本 1.1.1
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 3
常见问题

Improvement Orchestrator 是什么?

当需要一键跑完「生成→评分→评估→执行→门禁」全流程、失败后自动重试、或批量改进多个 skill 时使用。不用于单独评估 skill 质量(用 improvement-learner)或手动打分(用 improvement-discriminator)。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 136 次。

如何安装 Improvement Orchestrator?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install improvement-orchestrator」即可一键安装,无需额外配置。

Improvement Orchestrator 是免费的吗?

是的,Improvement Orchestrator 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Improvement Orchestrator 支持哪些平台?

Improvement Orchestrator 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Improvement Orchestrator?

由 _silhouette(@lanyasheng)开发并维护,当前版本 v1.1.1。

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