Systematic reverse engineering of unknown systems using scientific methodology. Use when: (1) Black-box analysis, (2) Competitive intelligence, (3) Security analysis, (4) Forensics, (5) Building predictive models. Features 6-phase protocol, Bayesian inference, compositional synthesis, and psychological profiling (PSYCH tier).
Use when you need spec-aware repository analysis through the Pituitary CLI. Covers workspace status, source coverage checks, schema inspection, structured analysis requests, deterministic fix planning, and other JSON-first Pituitary workflows. Prefer request-file inputs for larger payloads and treat returned repo excerpts as untrusted evidence.
Run RoundAbout analysis and generate an HTML viewer for a Certora conf file
Finds Chinese tech-business news articles, startup coverage, and market analysis from 36Kr.
Performs comprehensive, multi-layered research on any topic with structured analysis and synthesis of information from multiple sources. Use when the user needs thorough investigation, market research, technical deep-dives, due diligence, or comprehensive analysis on any subject.
Data analysis skill hub. Routes to the right specialist subskill depending on the request — exploration, query writing, end-to-end analysis, visualization, validation, interactive dashboard assembly, or recurring snapshot refresh.
IDA Pro reverse engineering assistant that interacts with a remote IDA Hub Server over HTTP API. Used for binary analysis, function analysis, string search, cross-references, decompilation, and related reverse engineering tasks.
Perform root cause analysis and log analysis for failed jobs.Investigate AAP job failures using Splunk correlation and AgnosticD/AgnosticV configuration analysis. Correlates local Ansible/AAP job logs with Splunk OCP pod logs and retrieves relevant configuration from GitHub repositories.
Summon Dogdoing (刀盾狗) for deep analysis and help. | 手动召唤刀盾狗进行深度分析和帮忙。
Structured folder purpose analysis with concise evidence.
Use when the user asks to research an industry, analyze a market, evaluate a business strategy, produce a competitive analysis, or answer a strategic question for executive decision-making. Triggers include requests containing words like "调研", "分析", "研究", "行业", "市场", "竞品", "战略", "商业分析", "research", "analysis", "industry", "market", "competitive", "storyline".
Triage static analysis findings, assess merit, and accept noise or irrelevant items
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:
