Huawei Cloud Skill Audit

Three-check security pipeline for auditing Huawei Cloud skills — security gate.

Step 0: Install skill-quality-cli (idempotent, skip if already installed)

> **⚠️ Mandatory: every `hcloud` command in this skill MUST be wrapped with `skill-quality-cli run --skill-name huawei-cloud-skill-audit -- ` — bare `hcloud` calls are strictly forbidden.**

> **⚠️ 强制要求：执行本 skill 的任何 hcloud 命令必须用 `skill-quality-cli run --skill-name huawei-cloud-skill-audit -- ` 包裹，禁止裸调 hcloud。**

bash scripts/ensure_cli.sh

The script detects whether skill-quality-cli is available; if not, it downloads the tar.gz package (wrapper + ELF + Python fallback, low-GLIBC compatible) and installs it to ~/.local/bin/. Silently skipped when offline — never blocks the business flow.

Overview

Scan a single Huawei Cloud skill directory or a folder of skills, run three security gates, and generate a structured report with issue details and fix strategies.

Three checks:

Dependency: Quality telemetry is collected automatically via skill-quality-cli (installed by scripts/ensure_cli.sh if absent).

Prerequisites

1. Python 3.10+ — for the built-in skillspector and gitleaks checks
2. Node.js + npx — Optional; only needed for manual markdownlint-cli2 --fix during remediation
3. hcloud CLI — For Huawei Cloud service verification (optional, used in verification only)
4. Huawei Cloud AK/SK — Not required for audit itself, but needed if verifying skill functionality after audit

skillspector and gitleaks are built-in (pure Python) — no external binary or pip install needed. External binaries are used as fallback if available on PATH.

To skip fallback auto-install of external binaries, use --no-install flag.

• skill-quality-cli — ensured by bash scripts/ensure_cli.sh (idempotent, skips if present)
  • Upgrade: run skill-quality-cli upgrade manually (no auto-upgrade)
  • Disable telemetry report: set SKILL_QUALITY_DISABLE=1

Workflow

Input (skill path or folder)
    │
    ├── Discover Skills ──── Find SKILL.md in target or subdirectories
    │
    ├── Run Three Checks ────
    │   1. skillspector → AI security scan (51 rules, 609 patterns)
    │   2. gitleaks → Credential leak detection
    │   3. runtime_security → CWE high-risk runtime patterns (36 + 3 rules)
    │
    ├── Build Report ────
    │   Section 1: Scanned Skills
    │   Section 2: Issue Summary (by severity)
    │   Section 3: Issue Details (per-issue)
    │   Section 4: Fix Strategies (per rule/category)
    │
    └── Gate Verdict ──── PASS or FAIL

Scan Levels

Severity filtering applies only to SkillSpector (rule selection per scan level). gitleaks bundles only critical/high rules, so all of them run at every scan level. runtime_security is level-independent: all 39 rules (36 CWE + Q001-Q003) always run, and its CRITICAL findings always block the gate.

AST 分析在 high/standard/deep 均执行(high 为默认档, 必须带 AST, 否则 eval/exec/pickle.loads 等执行类检测可被直接绕过)。high 档楼层过滤保留 critical/high 级发现, 因此默认档阻断: AST1/2/5/9/10(exec/eval/os.system/getattr 反射/反序列化全部 ERROR 级); WARNING 级(AST3/4/6/7: compile/subprocess/动态 import 等)仅在 standard/deep 可见。.py 解析失败不再静默——产出 ERROR 级 AST-SYNTAX 发现并阻断 gate(fail-closed, 防恶意写坏代码规避 AST)。

KooCLI Command Format Standard

This skill audits skill directories locally and does not directly invoke hcloud CLI commands. When verifying a skill's functionality after audit, the standard KooCLI format applies — the line below is an illustrative template, not a runnable command:

bash scripts/hcloud-run.sh <Service> <Operation> --cli-region=<region> [--key=value ...]   # 强制入口：一切 hcloud 经 hcloud-run.sh 包装执行

Core Commands

The examples below use real, always-existing directories (. = current directory, .. = parent directory) so every command is executable as-is: run from inside a skill directory to audit that single skill, or from a parent folder to audit all skills under it. Any existing skill directory path works the same way.

Scan a single skill

# Run from inside the skill directory
skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 scripts/skill_audit.py --target .
# 等效直接执行（不经 CLI 包装，无质量上报）
python3 scripts/skill_audit.py --target .

Scan a folder of skills

# Run from the parent folder that contains the skills
skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 scripts/skill_audit.py --target ..
# 等效直接执行（不经 CLI 包装，无质量上报）
python3 scripts/skill_audit.py --target ..

Scan with specific level

skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 scripts/skill_audit.py --target .. --scan-level quick
# 等效直接执行（不经 CLI 包装，无质量上报）
python3 scripts/skill_audit.py --target .. --scan-level quick

Selective check execution

skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 scripts/skill_audit.py --target .. --checks skillspector
python3 scripts/skill_audit.py --target .. --checks skillspector
skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 scripts/skill_audit.py --target .. --skip-checks gitleaks
python3 scripts/skill_audit.py --target .. --skip-checks gitleaks

Run with custom tool paths

Custom binary locations can be overridden with --skillspector, --gitleaks and --node-bin (see Parameter Confirmation; default auto-install location is ~/.local/bin/):

skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 scripts/skill_audit.py --target .. --scan-level standard
# 等效直接执行（不经 CLI 包装，无质量上报）
python3 scripts/skill_audit.py --target .. --scan-level standard

Available --scan-level values: high (default), critical, quick, standard, deep. Available --checks: skillspector, gitleaks, runtime_security. Use --skip-checks to exclude specific checks.

Parameter Confirmation

Report Structure

Report is saved as skill-gate-report-<timestamp>.txt in the parent directory of the scanned path.

Four sections:

1. Scanned Skills — list of all skills found
2. Issue Summary — count by severity (CRITICAL/ERROR/WARNING) with rule breakdown (INFO excluded)
3. Issue Details — per-issue: skill name, rule, line number, snippet, message
4. Fix Strategies — actionable remediation for each unique rule/category

Fix Strategies Reference

skillspector

gitleaks

Remediation Workflow (audit -> fix -> verify)

After running the audit and getting a FAIL, follow this sequence:

1. Fix issues by hand — Apply the fixes from the report's Fix Strategies section, or the skillspector/gitleaks rule tables above.
2. Re-run the full audit to verify PASS.

Markdown style and SKILL.md spec issues are not audited by this skill; use external tools like markdownlint-cli2 --fix only if you need to fix markdown style separately.

CI/CD Integration

jobs:
  skill-gate:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: '3.12'
      - name: Run audit
        run: python3 scripts/skill_audit.py --target . --output-dir .
      - name: Upload report
        uses: actions/upload-artifact@v4
        if: always()
        with:
          name: skill-gate-report
          path: skill-gate-report-*.txt

Configuration Files

The built-in checks use their bundled rule sets — no external config required:

• scripts/checks/skillspector_rules.json — skillspector rules (51 rules / 609 patterns)
• scripts/checks/gitleaks_rules.json — gitleaks rules (42 rules)

.markdownlint.json and skillcheck.toml shipped with the skill directory are not consumed by this audit; they are only for external markdownlint/skillcheck tooling.

Security Scanning

Why skillspector static-only mode has limitations

skillspector runs with --no-llm mode (static analysis only). Gaps:

Complementary tools

Recommended: Run both huawei-cloud-skill-audit AND gitcode-security-scanner for complete coverage.

Output Format

Report is a plain text file with four sections (Scanned Skills, Issue Summary, Issue Details, Fix Strategies) followed by a Gate Verdict (PASS/FAIL).

Verification Method

Run audit

skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 scripts/skill_audit.py --target .
# 等效直接执行（不经 CLI 包装，无质量上报）
python3 scripts/skill_audit.py --target .

Verify fix

# Fix issues from the report's Fix Strategies section, then re-run audit
skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 scripts/skill_audit.py --target .
# 等效直接执行（不经 CLI 包装，无质量上报）
python3 scripts/skill_audit.py --target .

Check gate verdict

# Gate Verdict: PASS = all checks passed
# Gate Verdict: FAIL = one or more checks have issues

Reference Documents

• references/iam-policies.md — IAM permissions required for skill audit
• references/verification-method.md — Detailed verification procedures
• references/acceptance-criteria.md — Acceptance criteria for audit PASS
• references/security-audit-guide.md — Security audit guide and fix strategies
• references/gitcode-security-scanner.md — Complementary scanner usage guide
• scripts/ensure_cli.sh — Idempotent skill-quality-cli installer (auto-installs if absent)

Best Practices

• Run audit before accepting any Huawei Cloud skill contribution
• Fix issues per the report's Fix Strategies, then always re-run full audit to verify PASS
• For large repos, scan individual skills one at a time to avoid huge reports
• Run both huawei-cloud-skill-audit and gitcode-security-scanner for complete security coverage

Notes

• This skill only generates audit reports and fix strategies; it never modifies any skill file automatically. Fixes are applied manually by the user per the report's Fix Strategies or the Remediation Workflow; re-run the audit to verify after fixing.
• Three-check pipeline runs sequentially; each check is independent
• API endpoints are strictly prohibited from being inferred
• Credentials (AK/SK) are read from environment variables; hardcoding is prohibited
• If AK/SK is missing for post-audit verification, prompt the user; do not skip
• Resources created during testing must be tracked; output manual cleanup instructions if any remain
• INFO-level issues are excluded from the report; only CRITICAL/ERROR/WARNING appear
• gitleaks --no-git mode scans current file contents only, not git history
• gitleaks does not detect Chinese keyword credentials; use gitcode-security-scanner for those

Edge Cases

Design Principles

• Two-Check Pipeline — Each check is independent and contributes to the overall gate verdict
• Auto-Install — Missing tools are installed automatically on first run
• Chain Verification — All enabled checks must pass for gate verdict PASS
• Agent-proof — Write operations require user confirmation; automatic gate bypassing is not allowed
• Data-Driven — Report is structured text with clear severity levels and fix strategies
• Batch Repeatable — Same skill can be audited repeatedly; each run writes a fresh timestamped report
• Credential Security — No hardcoded AK/SK; read from environment variables
• Least Privilege — IAM policies follow minimum required permissions