Twilio Voice and Video Android SDK development guide. Use when building native Android calling apps, configuring FCM push notifications, integrating ConnectionService, managing Android audio devices, setting up Gradle dependencies, handling runtime permissions, or testing on Android Emulator.
Use when writing, planning, continuing, repairing, revising, or running marathon/"疯狂写作"/auto continuation mode for Chinese long-form fiction with recurring characters, multiple plotlines, persistent world rules, chapter-by-chapter continuity needs, or style-specific constraints.
指导生成科研报告、行业调研、技术分析等需要深度研究的长篇报告。当任务目标是形成结构化、可引用、具有分析深度的正式报告时使用此技能。
Autonomous novel writing CLI agent with web workbench (InkOS Studio) - use for creative fiction writing, novel generation, style imitation, chapter continuation/import, EPUB export, AIGC detection, and fan fiction. Native English support with 10 built-in English genre profiles (LitRPG, Progression Fantasy, Isekai, Cultivation, System Apocalypse, Dungeon Core, Romantasy, Sci-Fi, Tower Climber, Cozy Fantasy). Also supports Chinese web novel genres (xuanhuan, xianxia, urban, horror, other). Multi-agent pipeline, two-phase writer (creative + settlement), 33-dimension auditing, token usage analytics, creative brief input, structured logging (JSON Lines), multi-model routing, custom OpenAI-compatible provider support, and InkOS Studio web UI for visual book management, chapter review, real-time writing progress, market radar, and analytics.
This skill should be used when the user asks to "make a game", "build a game", "generate a game", or wants to generate or update a complete Godot game from a natural language description. --- # Game Generator — Orchestrator Generate and update Godot games from natural language. ## Capabilities Read each sub-file from `${CLAUDE_SKILL_DIR}/` when you reach its pipeline stage. | File | Purpose | When to read | |------|---------|--------------| | `visual-target.md` | Generate reference image | Pipeline start | | `decomposer.md` | Decompose into task DAG | After visual target | | `scaffold.md` | Architecture + skeleton | After decomposition | | `asset-planner.md` | Budget and plan assets | If budget provided | | `asset-gen.md` | Asset generation CLI ref | When generating assets | | `rembg.md` | Background removal | Only when an asset needs transparency removed | | `task-execution.md` | Task workflow + commands | Before first task | | `quirks.md` | Godot gotchas | Before writing code | | *(godot-api skill)* | GDScript syntax ref | When unsure about GDScript syntax | | `scene-generation.md` | Scene builders | Targets include .tscn | | `test-harness.md` | Verification scripts | Before test harness | | `capture.md` | Screenshot/video | Before capture | | `visual-qa.md` | Visual QA (forked skill) | After capture | | `android-build.md` | APK export | User requests Android | ## Pipeline ``` User request | +- Check if PLAN.md exists (resume check) | +- If yes: read PLAN.md, STRUCTURE.md, MEMORY.md -> skip to task execution | +- If no: continue with fresh pipeline below | +- Generate visual target -> reference.png + ASSETS.md (art direction only) +- Analyze risks + define verification criteria -> PLAN.md +- Design architecture -> STRUCTURE.md + project.godot + stubs | +- If budget provided (and no asset tables in ASSETS.md): | +- Plan and generate assets -> ASSETS.md + updated PLAN.md with asset assignments | +- Show user a concise plan summary (risk tasks if any, main buil
Analyze stocks and companies using financial market data. Get company profiles, technical insights, price charts, insider holdings, and SEC filings for comprehensive stock research.
Local, crash-safe persistent memory for OpenClaw agents. SQLite-backed by default. Semantic search, projects, scopes, auto-capture. After installing or updating, run: palaia doctor --fix to complete setup.
Streaming chat assistant with conversation memory
McKinsey顾问式问题解决系统。从商业问题出发,通过假设驱动的结构化分析方法,生成McKinsey风格研究报告和PPT。融合Problem Solving方法论、MECE原则、Issue Tree拆解、Hypotheses形成、Dummy Page设计、智能数据收集和专业PPT生成能力。
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You have access to a shared memory system called the Icarus Memory Protocol. It stores memories as markdown files in ~/fabric/. Other agents on other platforms can read what you write. You can read what they wrote.
Fast headless browser for QA testing and site dogfooding. Navigate pages, interact with elements, verify state, diff before/after, take annotated screenshots, test responsive layouts, forms, uploads, dialogs, and capture bug evidence. Use when asked to open or test a site, verify a deployment, dogfood a user flow, or file a bug with screenshots. (gstack)
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:
