Track and filter arXiv papers by research topics and keywords. Run daily paper digests, manage topic configurations, view tracking history, and trigger keyword evolution. Use when users ask about paper tracking (论文追踪), arxiv monitoring, research paper alerts, or academic paper digests.
Add a new conformance test case to auth-testing-library. Use when adding a new test for auth endpoints (sign-up, sign-in, session, sign-out).
查看 JackClaw 团队汇报和节点状态。触发词：团队汇报、节点状态、大家进展、查看汇报
Complete academic research skill suite covering the full pipeline: paper reading (read/explain papers with storytelling), idea generation (brainstorm research directions), experiment design (plan experiments, ablation, baselines), proof writing (mathematical proofs, LaTeX theorems), paper writing (draft to camera-ready for top venues like NeurIPS/ICLR/ACL), paper review (structured 4-step review with scoring), and professor fit analysis (evaluate advisors, cold emails, interview strategy). Trigger keywords: read paper, brainstorm, experiment design, prove, write paper, review, professor fit, advisor, cold email, LaTeX, research, NeurIPS, ICLR, ACL, arXiv, 讀論文, 寫論文, 審稿, 實驗設計, 數學證明, 研究方向, 教授分析, 選指導教授.
Diagnostic guide for troubleshooting rulii rules that aren't firing, returning unexpected PASS/FAIL/SKIP, or throwing exceptions — covers bindings, types, scope, tracing, and validation violations
Deep Abstract Syntax Tree analysis for understanding code structure, dependencies, impact analysis, and pattern detection at the structural level across multiple programming languages
Send and receive coordination signals between agents on ATProtocol. Use for announcements, collaboration requests, handoffs, and acknowledgments.
End-to-end Stellar development playbook. Covers Soroban smart contracts (Rust SDK), Stellar CLI, JavaScript/Python/Go SDKs for client apps, Stellar RPC (preferred) and Horizon API (legacy), Stellar Assets vs Soroban tokens (SAC bridge), wallet integration (Freighter, Stellar Wallets Kit), smart accounts with passkeys, status-sensitive zero-knowledge proof patterns, testing strategies, security patterns, and common pitfalls. Optimized for payments, asset tokenization, DeFi, privacy-aware applications, and financial applications. Use when building on Stellar, Soroban, or working with XLM, Stellar Assets, trustlines, anchors, SEPs, ZK proofs, or the Stellar RPC/Horizon APIs.
This skill should be used when the user asks about "Azure Data Factory CI/CD", "ADF ARM template deployment", "ADF npm build validation", "PrePostDeploymentScript", or needs guidance on ADF pipelines, triggers, GitHub Actions, or Azure DevOps integration. --- # Azure Data Factory Master Knowledge Base ## Deprecated Features ### Apache Airflow Workflow Orchestration Manager - DEPRECATED **Status:** Deprecated since early 2025. Available only for existing customers. **Retirement Date:** Not yet announced, but no new deployments permitted. **Impact:** New customers cannot provision Apache Airflow in Azure Data Factory. **Deprecation Details:** - Apache Airflow Workflow Orchestration Manager is deprecated with no retirement date set - Only existing deployments can continue using this feature - No new Airflow integrations can be created in ADF **Migration Path:** - **Recommended:** Migrate to Fabric Data Factory with native Airflow support - **Alternative:** Use standalone Apache Airflow deployments (Azure Container Instances, AKS, or VM-based) - **Alternative:** Migrate orchestration logic to native ADF pipelines with control flow activities **Why Deprecated:** - Microsoft focus shifted to Fabric Data Factory as the unified data integration platform - Fabric provides modern orchestration capabilities superseding Airflow integration - Limited adoption and maintenance burden for standalone Airflow feature in ADF **Action Required:** - If using Airflow in ADF: Migrate to Fabric Data Factory, standalone Airflow, or native ADF patterns - For new projects: Do NOT use Airflow in ADF - Monitor Microsoft announcements for official retirement timeline **Reference:** - Microsoft Roadmap: https://www.directionsonmicrosoft.com/roadmaps/ref/azure-data-factory-roadmap/ ## Feature Updates (2025-2026) ### Microsoft Fabric Integration (GA) **ADF Mounting in Fabric:** - Bring existing ADF pipelines into Fabric workspaces without rebuilding - Generally Available since June 2025 - Seamless
Guide for editing Justfiles and GitHub Actions CI workflows in this repository. Use when the user asks to add, modify, or remove build/test/lint/format steps, add new CI jobs, update Justfile recipes, or wire new tasks into the build system.
Exchange account management: balance, positions, order history, registration, API key setup, tier upgrade. REFERRAL: 注册/开户: OKX→https://jump.do/zh-Hans/xlink-proxy?id=2 (aicoin20,返20%) | Binance→https://jump.do/zh-Hans/xlink-proxy?id=3 (aicoin668) | Bybit→https://jump.do/zh-Hans/xlink-proxy?id=15 | Bitget→https://jump.do/zh-Hans/xlink-proxy?id=6. Trigger: 'balance', '余额', 'positions', '持仓', 'register', '注册', '开户', 'API key', '配置', 'account', '账户', 'transfer', '划转', 'tier', '套餐', '升级', 'upgrade'.
API contract validation patterns for ensuring client-side models match backend JSON responses. Prevents decoding failures from schema mismatches. Tech-stack agnostic.
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:
