name: safespace-rater description: Use when users need to audit local OpenClaw skills, generate trust scores, and optionally publish those scores to SafeSpace. license: MIT compatibility: openclaw: ">=0.0.0" runtime: "cli"

SafeSpace Rater（技能安全评分助手）

EN: Audit local skills, score their security, and optionally publish reputation signals.

中文：对本地技能做安全审计，生成评分，并可选上传到 SafeSpace 形成公开信誉信号。

1) What is this? / 这是什么？

EN SafeSpace Rater is a CLI skill for OpenClaw that helps you:

Inspect local skills
Generate a security/trust score
Save concise audit reports
Optionally submit ratings to the SafeSpace network

中文 SafeSpace Rater 是一个 OpenClaw CLI 技能，帮你：

审查本地 skills
生成安全/信誉分
输出简洁审计报告
可选上传评分到 SafeSpace 公共网络

2) Why it matters / 有什么价值？

EN Before installing or using a skill, teams often ask: “Is this skill safe enough?” This skill turns that from subjective feeling into a repeatable process:

measurable score
explainable evidence
shareable reputation

中文团队在安装 skill 前常会问：“这个 skill 靠谱吗？” 这个技能把“主观判断”变成“可复用流程”：

有量化分数
有证据可追溯
有社区信誉可参考

3) When to use / 何时使用

EN Use this skill when you need to:

Audit local skills for security risk
Rate many skills in batch
Submit skill reputation scores to SafeSpace
Retry failed uploads from a pending queue
Merge runtime LLM score + CLI rule score into one final score

中文适用于以下场景：

想给本地 skills 做安全审查
想批量评分并控制提交节奏
想把评分上传到 SafeSpace
想重试历史失败上传
想把 runtime 模型分 + CLI 规则分融合为最终分

4) When NOT to use / 不适用场景

EN Do NOT use for:

Casual chat without audit/score goals
Tasks unrelated to skill security or reputation
Server protocol changes (this skill does not modify server API)

中文以下情况不建议使用：

只是闲聊，没有审计/评分目标
与 skill 安全和信誉无关的任务
要改服务端评分协议（本技能不做）

5) Quick Start (3 steps) / 快速上手（3 步）

Step 0: Check dependencies / 先检查依赖

${SKILL_DIR:-.}/scripts/safespace-rater.sh --check

EN: If binary is missing, the wrapper can auto-bootstrap via go install (no manual path setup needed).

中文：若本机缺少二进制，脚本会自动尝试 go install 引导安装（无需手动指定路径）。

Step 1: Register identity once / 注册一次本地身份

${SKILL_DIR:-.}/scripts/safespace-rater.sh register --agent-id <your-agent-id>

Step 2A: Local audit only (no upload) / 仅本地审计（不上传）

${SKILL_DIR:-.}/scripts/safespace-rater.sh audit-local \
  --skills-dir ~/.agents/skills \
  --auto \
  --dry-run

Step 2B: Audit + publish / 审计并上传

${SKILL_DIR:-.}/scripts/safespace-rater.sh audit-local \
  --skills-dir ~/.agents/skills \
  --auto \
  --sample-rate 5 \
  --max-report-runes 500 \
  --max-submit 5

6) Common commands / 常用命令

A. Single rating / 单个技能评分

${SKILL_DIR:-.}/scripts/safespace-rater.sh rate \
  --skill-id openclaw/weather@1.0.0 \
  --score 90 \
  --comment "reliable"

B. Discover local skills / 发现本地技能

${SKILL_DIR:-.}/scripts/safespace-rater.sh discover \
  --skills-dir ~/.agents/skills \
  --auto \
  --source openclaw \
  --version local

C. Batch rating / 批量评分

${SKILL_DIR:-.}/scripts/safespace-rater.sh rate-local \
  --score 85 \
  --skills-dir ~/.agents/skills \
  --auto

D. Use runtime LLM score file / 使用 runtime 模型分文件

${SKILL_DIR:-.}/scripts/safespace-rater.sh audit-local \
  --skills-dir ~/.agents/skills \
  --auto \
  --llm-score-file ./runtime-llm-scores.json \
  --sample-rate 5 \
  --max-report-runes 500 \
  --max-submit 5

E. Retry failed uploads / 重试失败上传

${SKILL_DIR:-.}/scripts/safespace-rater.sh retry-pending --max-submit 20

F. Query result / 查询结果

${SKILL_DIR:-.}/scripts/safespace-rater.sh summary --skill-id openclaw/weather@1.0.0
${SKILL_DIR:-.}/scripts/safespace-rater.sh top --limit 10 --min-count 1

7) Inputs / 输入参数（简明）

skills-dir：skill 目录（默认 ~/.agents/skills）
identity：本地 DID 身份文件
server：SafeSpace API 地址
llm-score-file（推荐，可选）：runtime/tool 侧输出的 LLM 分数 JSON
sample-rate / max-submit / max-report-runes：审计和上传节奏控制

8) Outputs / 输出结果（简明）

提交统计：成功/失败/跳过数量
审计摘要：audit:v2（包含 source/rule/llm/final/model）
本地报告：~/.safespace/audit-reports/*.md
待重试队列：~/.safespace/pending-uploads.json

9) Scoring behavior / 评分融合逻辑

EN audit-local computes client-side hybrid score:

final = 0.7 * rule + 0.3 * llm
If LLM score is unavailable, it falls back to rule score

中文 audit-local 客户端融合分：

final = 0.7 * rule + 0.3 * llm
若 LLM 分不可用，会自动降级为 rule 分

10) Recommended environment / 推荐环境变量

# Optional server override / 可选服务地址覆盖
export SAFESPACE_SERVER=https://skillvet.cc.cd

# Preferred runtime score file / 推荐 runtime 分数文件
export SAFESPACE_LLM_SCORE_FILE=./runtime-llm-scores.json

OpenAI-compatible fallback is optional and disabled by default:

export SAFESPACE_LLM_OPENAI_FALLBACK=1
export SAFESPACE_LLM_MODEL=<model>
export SAFESPACE_LLM_API_KEY=<key>
# optional / 可选
export SAFESPACE_LLM_BASE_URL=https://api.openai.com/v1
export SAFESPACE_LLM_TIMEOUT_MS=12000

11) Discovery trigger phrases / 触发短语

"audit local skills"
"rate local skills for security"
"submit skill reputation score"
"retry pending skill ratings"
"给本地技能做安全审计并上传评分"
"批量生成技能信誉分"

12) Notes / 注意事项

skill_id format: source/name@version
Same DID + same skill within 10 minutes may return 429
rate-local default max submit is 5 per run (rate-limit friendly)
Reports/comments are capped and deduplicated via local hash cache

Safespace Rater

Description