Universal legal document processor with PII anonymization. Anonymize → Work → Deanonymize. Modes: MEMO (legal analysis), REDLINE (tracked changes in contract), SUMMARY (brief overview), COMPARISON (diff two docs), BULK (up to 5 files). Supports .docx and .pdf input. Trigger for: contract review, risk analysis, compliance check, GDPR review, clause analysis, tracked changes, redline, 'anonymize', 'pii shield'. If user uploads contract/NDA/DSAR/HR doc — USE THIS SKILL. If user says 'skip pii' or 'don't anonymize' — skip anonymization and work directly.
Local-first analytics for AI agent skills. Use when user asks about skill usage, analytics, health, context budget, or wants to clean up unused skills.
- 📄 agent-guide.md
- 📄 analyze.md
- 📄 diff.md
Manage and run builtin analysis skills against Nsight Systems profiles.
Analyze comp titles, genre trends, pricing strategies, and market positioning
- 📁 assets/
- 📁 references/
- 📁 scripts/
- 📄 SKILL.md
Wire OpenClix events to an installed product analytics provider (Firebase, PostHog, Mixpanel, or Amplitude) and produce pre/post campaign impact reports centered on 7-day retention. TRIGGER when the user asks to "connect analytics", "measure campaign impact", "check retention", "tag OpenClix events", or wants to know whether campaigns are working — even if they say "are my notifications helping?" without mentioning analytics. DO NOT trigger for campaign config changes based on metrics — that belongs to openclix-update-campaigns.
Smart Blog 品質分析。5 大類 100 分評分，包含 Humanizer 29 模式 AI 偵測、 SEO 驗證、E-E-A-T 評估、PageSpeed 整合。支援 PDF 報告輸出。 Use when user says "analyze blog", "分析文章", "blog audit", "品質評分", "smart-blog analyze", "blog analyze".
- 📁 demo/
- 📁 docs/
- 📁 tests/
- 📄 analyze.sh
- 📄 fetch.sh
- 📄 README.md
VOC AI — Amazon Review Intelligence. Input an ASIN, fetch real Amazon reviews via Shulex VOC API and run AI analysis. Outputs a structured bilingual report: sentiment breakdown, top pain points, key selling points, and Listing optimization suggestions. Triggers: voc, amazon review analysis, asin analysis, voice of customer, listing optimization, pain points, selling points, review insights, amazon fba, product research
- 📁 references/
- 📁 scripts/
- 📄 README.md
- 📄 SKILL.md
Amazon seller data analysis tool. Features: market research, product selection, competitor analysis, ASIN evaluation, pricing reference, category research. Uses scripts/apiclaw.py to call APIClaw API, requires APICLAW_API_KEY. --- # APIClaw — Amazon Seller Data Analysis > AI-powered Amazon product research. Respond in user's language. ## Files | File | Purpose | |------|---------| | `scripts/apiclaw.py` | **Execute** for all API calls (run `--help` for params) | | `references/reference.md` | Load when you need exact field names or filter details | ## Credential
- 📁 assets/
- 📁 references/
- 📁 scripts/
- 📄 SKILL.md
Analyze Linux kernel vulnerabilities from KASAN/UBSAN/BUG crash logs or CVE descriptions. Performs full root cause analysis, exploitability assessment, patch development, and verification. Use this skill whenever the user provides a kernel crash log, KASAN report, kernel panic trace, syzbot report, or asks to analyze/patch a kernel vulnerability. Also trigger when the user mentions kernel CVEs, kernel exploit analysis, kernel bug triage, or wants to understand if a kernel bug is exploitable. Even if the user just pastes a raw stack trace from dmesg, this skill applies. --- # Kernel Vulnerability Analyzer A comprehensive skill for analyzing Linux kernel vulnerabilities — from crash log triage through root cause analysis, exploitability assessment, patch development, and verified fix delivery. This skill is designed around a **hive-mode subagent architecture**: break the analysis into parallel workstreams, plan before executing, and coordinate results across agents. ## Core Workflow Overview The analysis follows seven phases. Each phase builds on the previous, but many sub-tasks within a phase can run in parallel via subagents. ```
Deep Abstract Syntax Tree analysis for understanding code structure, dependencies, impact analysis, and pattern detection at the structural level across multiple programming languages
- 📁 examples/
- 📄 MICROSIMULATION_REFORM_GUIDE.md
- 📄 SKILL.md
Common analysis patterns for PolicyEngine research repositories (CRFB, newsletters, dashboards, impact studies). For population-level estimates (cost, poverty, distributional impacts), use the policyengine-microsimulation skill instead. --- # PolicyEngine analysis Patterns for creating policy impact analyses, dashboards, and research using PolicyEngine. **For population-level estimates** (budgetary cost, poverty impact, distributional analysis), use the **policyengine-microsimulation** skill instead. This skill covers analysis repo patterns, visualization, and household-level calculations. See `MICROSIMULATION_REFORM_GUIDE.md` for UK-specific microsimulation patterns. ## For Users ### What are Analysis Repositories?
Use this skill whenever the user wants to extract architecture diagrams from academic papers, filter out invalid images, analyze the structure and components of diagrams, automatically match suitable color schemes, or says "提取论文架构图", "架构图分析", "从PDF中提取图表", "自动分析架构图", "architecture diagram extraction", "extract figures from pdf", "analyze architecture diagram".
