Comprehensive EDA on scientific data files — structure, content, quality, and characteristics analysis across 200+ formats. Use when analyzing any data file to understand its structure, quality, and downstream analysis recommendations.
High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data. Use for CSV/JSON/Parquet processing, statistical analysis, time series, and creating charts.
Performs competitor research and generates detailed analysis reports with market positioning insights. Covers feature comparison, pricing analysis, SWOT, and strategic recommendations.
Use before any creative work or significant changes. Activates on "brainstorm", "let's brainstorm", "deep analysis", "analyze this feature", "think through", "help me design", "explore options for", or when user asks for thorough analysis of changes, features, or architectural decisions. Guides collaborative dialogue to turn ideas into designs through one-at-a-time questions, approach exploration, and incremental validation.
Investigate incidents, debug performance issues, analyze logs, and manage observability resources in Dynatrace using the dtctl CLI. Use this skill whenever the user asks about error rates, latency spikes, service health, crash-looping pods, web vitals, SLO status, open problems, root cause analysis, log patterns, trace analysis, or building dashboards — even if they don't mention Dynatrace by name. Also covers DQL queries, workflow management, notebook and dashboard creation, settings configuration, and any operations against a Dynatrace environment.
Token-efficient smart contract security auditing via Behavioral State Analysis (BSA). Scopes analysis to contract type, runs only relevant threat engines, and uses tiered output depth. Use for auditing smart contracts, security reviews, or DeFi threat modeling.
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.
Manage and run builtin analysis skills against Nsight Systems profiles.
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
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. ```
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?
Master workflow skill for City of Boston policy analysis and civic innovation. ALWAYS use this skill for any request involving Boston city data, city services, neighborhood equity, public policy, government performance, 311 analysis, housing, safety, transportation, or any civic issue — even if the user hasn't explicitly asked for a 'full analysis'. This skill orchestrates five sub-skills: city-problem-framing (Bloomberg-inspired), city-policy-analysis (J-PAL-inspired), city-communication (GovLab/InnovateUS-inspired), city-benchmarking (cross-city comparison using San Francisco, Seattle, and DC data), and city-performance-management (Results for America / PerformanceStat). Use this skill for: 'full analysis', 'policy brief', 'data-driven recommendation', 'city improvement project', 'investigate [issue]', 'compare Boston to other cities', 'what does the data show', 'help me write a memo about', or any request that combines problem definition, data analysis, and communication for government or civic purposes.
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)
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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:
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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.
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We try to avoid that. Use ranking + comments to surface better skills:
