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在 OpenClaw 中安装
/install quality-boost
功能描述
通过9条严格规则系统评估并量化大模型回答质量，防止幻觉、跑偏、冗长和遗漏，确保准确、简洁、合规的输出。
安全使用建议
This skill is an instruction-only prompt/template pack and appears to do what it says. Before applying it globally: (1) review the system-inject content — injecting it will prepend a system prompt that affects all agent responses; (2) back up ~/.openclaw/config.json before making changes so you can revert; (3) prefer manual invocation or session-level use first (use the quick-apply templates) to confirm the behavior meets your needs before enabling autoApply/system injection; (4) never paste the templates into external services unless you intend those services to adopt the rules. No credentials or external downloads are required.
能力评估
Purpose & Capability
Name/description (improving LLM answer quality) matches the provided materials: 9 rules, templates, quick-apply snippets, and a system-prompt file. The skill requires no binaries, env vars, or external services — all requested resources are consistent with a prompt/policy helper.
Instruction Scope
SKILL.md and supporting files are a set of prompts and templates to be applied to conversations. They remain within the stated scope, but include an explicit 'system injection' template and instructions for adding a system prompt. That changes agent behavior globally if applied; it's expected for this purpose but broadens the skill's runtime impact (affects all future responses when injected).
Install Mechanism
No install spec or external downloads — instruction-only. No code files to execute, and the regex scanner had nothing to analyze, so no installation risk was found.
Credentials
No environment variables, credentials, or unrelated config paths are requested. The only file path referenced is ~/.openclaw/config.json and a skill file under ~/.openclaw/skills — proportional to the stated goal of optionally persisting behavior.
Persistence & Privilege
The skill does not force 'always: true', but it provides instructions to modify the user's OpenClaw config (systemPrompt prepend and an autoApply example). Writing to the agent's own config to persist a system prompt is coherent for this skill, but it is a persistent change that will affect future agent behavior until the user reverts it.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install quality-boost - 安装完成后，直接呼叫该 Skill 的名称或使用
/quality-boost触发 - 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
v1.0.0
质量评估版：质量检测工具、评分标准、A/B测试方法、持续优化建议
元数据
常见问题
Quality Boost - 大模型回答质量提升器 是什么？
通过9条严格规则系统评估并量化大模型回答质量，防止幻觉、跑偏、冗长和遗漏，确保准确、简洁、合规的输出。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 100 次。
如何安装 Quality Boost - 大模型回答质量提升器？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install quality-boost」即可一键安装，无需额外配置。
Quality Boost - 大模型回答质量提升器 是免费的吗？
是的，Quality Boost - 大模型回答质量提升器 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Quality Boost - 大模型回答质量提升器 支持哪些平台？
Quality Boost - 大模型回答质量提升器 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 Quality Boost - 大模型回答质量提升器？
由 jjx（@jx-76）开发并维护，当前版本 v1.0.0。
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