Safespace Rater

Use when users need to audit local OpenClaw skills, generate trust scores, and optionally publish those scores to SafeSpace.

Security Scan

The skill's files and runtime instructions are internally consistent with an auditing/rating CLI: it scans local skill folders, produces reports, and can optionally submit ratings to a remote SafeSpace server; the only notable risks are the auto-bootstrap step (go install of a third‑party repo) and the default remote server endpoint, both of which are expected for this functionality but worth verifying before use.

Purpose & Capability

Name/description, SKILL.md, and the shell wrapper align: the skill is a CLI that audits local skills, creates reports, and can publish ratings. The wrapper simply locates or bootstraps a safespace-rater binary and then execs it — this is coherent with the stated purpose.

Instruction Scope

SKILL.md instructs the agent to read a local skills directory (~/.agents/skills by default), optionally read a runtime LLM score file, register a local identity, and write reports to ~/.safespace. Those actions are within the scope of an auditing/rater tool and do not request unrelated system-wide data or credentials. The doc does advertise optional submission to a remote server (SAFESPACE_SERVER).

Install Mechanism

There is no registry install spec, but the included script will attempt to auto-bootstrap the runtime via 'go install' using GO_INSTALL_SPEC (github.com/vpn2004/SkillVet/cmd/safespace-rater@latest) or build from a repo root. Using 'go install' of a third-party repository is a common pattern but is moderate risk because it will fetch and compile remote code. The URL is a normal GitHub-style import path (not an arbitrary IP or pastebin).

Credentials

The skill declares no required env vars; SKILL.md documents optional envs (SAFESPACE_SERVER, SAFESPACE_LLM_* and an OpenAI API key fallback). These optional variables are relevant to the advertised features (server endpoint, LLM fallback). However, providing an API key or allowing uploads will expose data to the chosen server — the default SAFESPACE_SERVER value (https://skillvet.cc.cd) looks nonstandard and should be verified before use.

Persistence & Privilege

The skill is not always-enabled, does not request elevated platform privileges, and does not modify other skills' configs. It writes local outputs under ~/.safespace and registers a local DID identity as expected for its function.

Assessment

This skill appears to do what it says (audit local skills, produce reports, and optionally publish ratings). Before installing or running it: 1) Inspect the Go repository it may 'go install' (github.com/vpn2004/SkillVet) or build the binary yourself rather than auto‑installing compiled code fetched from the network. 2) Verify the SAFESPACE_SERVER endpoint — the default domain is uncommon; if you will publish ratings, point it to a known/trusted server. 3) If you don't want data leaving your machine, run audit-local with upload/publish flags disabled (dry-run) and avoid exporting SAFESPACE_LLM_API_KEY or other credentials. 4) Review the Go binary source (if possible) or build it in a sandbox/container to limit blast radius. 5) Consider running the tool on a copy of your skills directory first to confirm outputs and behavior.

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:

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

中文 SafeSpace Rater 是一个 OpenClaw CLI 技能，帮你：

1. 审查本地 skills
2. 生成安全/信誉分
3. 输出简洁审计报告
4. 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