cheat-on-content
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
Static Application Security Testing (SAST) tool setup, configuration, and custom rule creation for comprehensive security scanning across multiple programming languages.
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill sast-configuration --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/sast-configurationContext preview
The summary Claude sees to decide when to auto-load this skill.
Static Application Security Testing (SAST) tool setup, configuration, and custom rule creation for comprehensive security scanning across multiple programming languages.
name: sast-configuration description: "Static Application Security Testing (SAST) tool setup, configuration, and custom rule creation for comprehensive security scanning across multiple programming languages." risk: unknown source: community date_added: "2026-02-27"
Static Application Security Testing (SAST) tool setup, configuration, and custom rule creation for comprehensive security scanning across multiple programming languages.
1. Identify languages, repos, and compliance requirements. 2. Choose tools and define a baseline policy. 3. Integrate scans into CI/CD with gating thresholds. 4. Tune rules and suppressions based on false positives. 5. Track remediation and verify fixes.
This skill provides comprehensive guidance for setting up and configuring SAST tools including Semgrep, SonarQube, and CodeQL.
1. Identify primary programming languages in your codebase 2. Determine compliance requirements (PCI-DSS, SOC 2, etc.) 3. Choose SAST tool based on language support and integration needs 4. Review baseline scan to understand current security posture
# Semgrep quick start pip install semgrep semgrep --config=auto --error # SonarQube with Docker docker run -d --name sonarqube -p 9000:9000 sonarqube:latest # CodeQL CLI setup gh extension install github/gh-codeql codeql database create mydb --language=python
# GitHub Actions example
- name: Run Semgrep
uses: returntocorp/semgrep-action@v1
with:
config: >-
p/security-audit
p/owasp-top-ten# .pre-commit-config.yaml
- repo: https://github.com/returntocorp/semgrep
rev: v1.45.0
hooks:
- id: semgrep
args: ['--config=auto', '--error']1. **Start with Baseline**
2. **Incremental Adoption**
3. **False Positive Management**
4. **Performance Optimization**
5. **Team Enablement**
./scripts/run-sast.sh --setup --language python --tools semgrep,sonarqube
# See references/semgrep-rules.md for detailed examples
rules:
- id: hardcoded-jwt-secret
pattern: jwt.encode($DATA, "...", ...)
message: JWT secret should not be hardcoded
severity: ERROR# PCI-DSS focused scan semgrep --config p/pci-dss --json -o pci-scan-results.json
| Tool | Best For | Language Support | Cost | Integration | |------|----------|------------------|------|-------------| | Semgrep | Custom rules, fast scans | 30+ languages | Free/Enterprise | Excellent | | SonarQube | Code quality + security | 25+ languages | Free/Commercial | Good | | CodeQL | Deep analysis, research | 10+ languages | Free (OSS) | GitHub native |
1. Complete initial
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Repo: LiHongwei-cn/lihongwei-cn
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
提议并执行 rubric 或 bucket 升级。两种模式:**完整 rubric bump**(最高风险动作,5 步强制 + 跨模型审核)和 **--bucket-only 轻量重校**(只换 bucket 边界,不动 rubric 公式)。**Phase 2 强制走 cheat-score-blind…
cheat-on-content 的首次 onboarding 与脚手架创建器。统一流程——所有用户都走相同 5 阶段闭环,唯一区别是"发过视频的人"会在 init 时多一步:抓取已有视频建立历史 context(用于后续 cheat-seed 给更贴合的选题、更准的…
从对标账号导入 script + 数据 → 拆 pattern + 派生 base rubric 信号 → 写到 benchmark.md / script_patterns.md / rubric_notes.md。**这是工具最早期信号的来源**——cold-start…
把老用户的 .cheat-state.json 升级到当前 schema_version。读 migrations/registry.md 算迁移链,按顺序应用每一步迁移文件。幂等:跑两次结果一样。失败停在中间版本不前进。触发词:"迁移"/"升级 state"/"migrate"/"我的 state…
从复盘评论数据派生 / 刷新账号的受众画像,写入 audience.md。这是和 rubric 平行的第二个派生物——rubric 答"怎么打分",persona 答"谁在看"。cheat-seed 选题 / 写稿时读它。**audience.md 含实绩信号,cheat-score-blind…