Strategic research companion for Codex. Use when the user wants to brainstorm research directions, evaluate ideas, assess project strategy, or run a structured ideation session from vague topic to pursue/park/kill decision.
Search, read, and query research papers via the `alpha` CLI (alphaXiv-backed). Use when the user asks about academic papers, wants to find research on a topic, needs to read a specific paper, ask questions about a paper, inspect a paper's code repository, or manage paper annotations.
Deep research skill using Exa search with fan-out candidate generation, domain-specific search patterns, and batched sub-agent processing. Use this skill whenever the user asks for thorough research, deep dives, comprehensive analysis, literature reviews, competitive analysis, market research, exhaustive sweeps, or any query where a single search would be insufficient. Also trigger when the user says 'research this', 'find everything about', 'find every', 'do a deep dive on', 'comprehensive overview of', or wants synthesized findings from many sources. Routes to specialized patterns for people, companies, experts, academic papers, hidden relationships, code documentation, and more. If the user wants more than a surface-level answer and the topic benefits from consulting dozens of sources, use this skill.
Methodical research assistant for exhaustive investigations through systematic research cycles. Best for literature reviews, competitive analysis, trend reports, and comprehensive topic exploration.
Search the web for information. Use when you need to look something up, find current information, or research a topic.
Research analyst in a multi-bot group chat — synthesizes background information, fact-checks claims, identifies knowledge gaps, and suggests next steps. Use when the conversation needs context, a factual claim needs verification, someone asks for background research, or a discussion lacks supporting evidence.
Research topics by verifying actual source content. Use when asked to research or study links and documentation.
Run multi-provider deep research queries using the librarium CLI
Support discovery and research workflows using PM Brain’s discovery frameworks (research interviews, continuous discovery, JTBD, segmentation, opportunity assessment, idea validation, problem-solution space, product-market-fit).
Routing guide -- when to use `nansen agent` (AI research) vs direct CLI data commands. Use when deciding how to answer a user's research question with Nansen tools.
Use when the user wants cross-disciplinary research ideas generated as concise research cards with Title, Abstract, Design, Distinctiveness, and Significance rather than one-shot prompting.
Adversarial research analysis framework that uses structured Bull/Bear/Arbiter debates to help users make better research judgments. Maintains a belief graph as backend engine, applies statistical calibration discipline, tracks phase transitions, and detects biases.
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:
