Generate and analyze AI Bill of Materials (AIBOM) for Python projects using AI/ML components. Identifies AI models, datasets, tools, and frameworks for security and compliance tracking.
Full KYC customer onboarding with mandatory Step 0 independent verification (5+1 searches), 17 sequential stagegates requiring explicit analyst consent, deterministic four-factor risk scoring, case folder auto-creation, 4-sheet Excel dashboard, 17-section PDF report, and immutable audit trail. Covers UK/EU (AMLD5), US (FinCEN CDD), and MENA jurisdictions.
AEO (Answer Engine Optimization) monitoring and analysis using canonry CLI and aeo-audit tool. Use when: (1) running citation sweeps across AI providers (Gemini, ChatGPT, Claude, Perplexity); (2) auditing technical SEO with structured data validation; (3) implementing schema markup, sitemaps, llms.txt; (4) diagnosing indexing issues via Google Search Console and Bing Webmaster Tools; (5) optimizing content for AI readability and entity consistency. NOT for: general web development, content writing, PPC campaigns, or social media management.
Preflight security scanner for AI coding agents — scans deployment config, skills/MCP servers, memory/sessions, and AI agent config files (hooks injection) for secrets, PII, prompt injection, and dangerous patterns. Runs 4 model behavior probes (persuasion, sandbagging, deception, hallucination). Supports LLM-enhanced semantic analysis. Works with OpenClaw, Claude Code, Cursor, and Codex. Use when a user asks for a security audit, health check, or wants to scan their AI agent setup for vulnerabilities.
Generate all orchestrator report types — execution summaries, agent performance, workflow analytics, health, config audit, and HTML dashboard with charts. Use after task runs or for project status overview.
Comprehensive accessibility audit to identify WCAG compliance issues and barriers to inclusive design.
Analyze pull requests and diffs for bugs, security vulnerabilities, performance issues, style violations, and test coverage gaps — producing structured, actionable feedback
高德地图 JSAPI v2.0 (WebGL) 开发技能。涵盖地图生命周期管理、强制安全配置、3D 视图控制、覆盖物绘制及 LBS 服务集成。
This skill should be invoked BEFORE presenting implementation plans, architecture recommendations, code review findings, or answers to broad technical questions. Use proactively when about to "recommend", "suggest", "propose", "design", "plan", or answer "how should", "what's the best way", "which approach". MANDATORY for multi-file changes, refactoring proposals, and security-sensitive recommendations.
Audit all table and figure captions for language, notation, and formatting consistency
企业级AI提示词全生命周期开发规范，包含需求设计、开发编写、版本管控、测试验收、安全合规全流程，适用于企业级提示词项目开发
[](https://oathe.ai/report/joylarkin/openclaw-security-news)
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
