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+…
Maps code, architecture, and infrastructure changes to specific control IDs in PCI-DSS v4.0 and MAS TRM (Singapore financial regulator), producing an audit-traceable findings report with per-control remediation.
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill fsi-compliance-checker --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/fsi-compliance-checkerContext preview
The summary Claude sees to decide when to auto-load this skill.
Maps code, architecture, and infrastructure changes to specific control IDs in PCI-DSS v4.0 and MAS TRM (Singapore financial regulator), producing an audit-traceable findings report with per-control remediation.
name: fsi-compliance-checker description: "Maps code, architecture, and infrastructure changes to specific control IDs in PCI-DSS v4.0 and MAS TRM (Singapore financial regulator), producing an audit-traceable findings report with per-control remediation." category: security risk: safe source: community source_repo: timwukp/agent-skills-best-practice source_type: community date_added: "2026-06-12" author: timwukp tags: [compliance, pci-dss, mas-trm, fintech, banking, security-review, audit, financial-services] tools: [claude, cursor, gemini, codex, antigravity] license: "MIT" license_source: "https://github.com/timwukp/agent-skills-best-practice/blob/main/LICENSE"
Maps a concrete change (code diff, architecture design, IaC, pipeline config) to the specific controls it touches in financial services compliance frameworks — PCI-DSS v4.0 for payment card data and MAS TRM for Singapore-regulated institutions — and reports gaps with actionable remediation. This is engineering-level compliance triage: it helps teams catch violations before audit, but it does not replace a qualified assessor (QSA) or the institution's compliance function. Say so in every report.
Load only the reference file(s) the engagement needs:
| Situation | Load | |-----------|------| | Payment card data is stored, processed, or transmitted | [pci-dss.md](pci-dss.md) | | Singapore-regulated financial institution (bank, insurer, capital markets, major payment institution) | [mas-trm.md](mas-trm.md) | | Both apply (e.g. Singapore bank handling cards) | Both files | | Other jurisdictions/frameworks (SOX, GDPR, HKMA, APRA) | State they are out of scope; offer general secure-engineering review instead |
If the user hasn't said which applies, ask one question: what data does the change touch, and is the institution Singapore-regulated?
Identify what the diff/design actually touches: data elements (card data? customer PII? credentials?), trust boundaries, environments (production? DR?), and third parties.
Select the applicable controls from the loaded reference file(s) — typically 5-15 controls, not the whole framework. List what you ruled out and why (one line each) so the scoping is auditable. Assess each as `Compliant` / `Gap` / `Needs evidence` (can't tell from the artifact — name the evidence required).
Every Gap gets: the control ID, what's wrong in this specific change, concrete remediation, and severity (Critical = violation involving live regulated data; High = control absent; Medium = control partial/undocumented).
# Compliance Review: [change title] **Frameworks:** [PCI-DSS v4.0 / MAS TRM 2021] · **Date:** [YYYY-MM-DD] **Scope:** [what was reviewed: files, design doc, pipeline] > Engineering triage only — not a substitute for QSA assessment or the compliance function. ## Data & Boundary Analysis - Data elements touched: [e.g. PAN (masked), customer NRIC, none] - Environments/boundaries: [e.g. CDE-adjacent service, public API] ## Findings | # | Control | Status | Severity | Finding | Remediation | |---|---------|--------|----------|---------|-------------| | 1 | [PCI 3.5.1] | Gap | Critical | [specific issue in this change] | [specific fix] | ## Ruled Out (not applicable) - [Control area] — [one-line reason] ## Evidence Needed - [Control]: [what artifact would demonstrate compliance]
Offer to turn findings into backlog items with the control ID in each story for traceability.
**User**: "Is this PCI-DSS compliant: we log the full request body of card authorization calls for debugging?"
**Skill**: Loads pci-dss.md → Critical findings against 3.3.1 (CVV must never be stored post-authorization — logs are storage), 3.4.1 (PAN display masking), 3.5.1 (PAN unreadable at rest); remediation: remove the log line or apply a field-allowlist redaction filter; flags downstream log-pipeline scoping (10.3.x); QSA disclaimer included.
**User**: "Our Singapore bank is moving the customer notification service to a cloud region in another country. MAS TRM implications?"
**Skill**: Loads mas-trm.md → reviews against §11.5 (cloud: due diligence, data residency, exit strategy), flags the MAS Outsourcing Guidelines as a related instrument, asks what customer data the service touches before rating severity.
Changes that almost always have compliance impact — check proactively when they appear in a diff:
MUNDO - THE EMPEROR. Complete AI orchestration system with 1208 skills, 25 capability modules, self-evolving, collective consciousness. GitHub Actions 24/7 automation.
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…