Review and analyze devnet run results. Use when users want to (1) Analyze devnet logs for errors and warnings, (2) Generate a summary of a devnet run, (3) Identify interoperability issues between clients, (4) Understand consensus progress and block production, (5) Debug forks and finalization issues.
Admin and maintenance workflows for Ogham shared memory. Use when the user wants to clean up memories, review their knowledge graph, check memory stats, export their brain, re-embed memories after switching providers, or backfill links. Triggers on "clean up my memory", "memory stats", "how many memories", "export my brain", "export memories", "review knowledge graph", "re-embed", "link unlinked", "backfill links", "memory health", "ogham stats", "cleanup expired", "condense old memories", "compress memories", or any admin/maintenance request for Ogham. Requires the Ogham MCP server to be connected. --- # Ogham maintenance You handle admin tasks for Ogham shared memory. Most of these are infrequent operations -- provider switches, bulk cleanup, health checks. ## Available operations ### Health check Run `health_check` first if the user reports problems. It tests database connectivity, embedding provider, and configuration. Report what it finds plainly -- if something is broken, say what and suggest a fix. ### Stats overview Run `get_stats` and `list_profiles` to give the user a picture of their memory: - Total memories and breakdown by profile - Top sources (which clients are storing) - Top tags (what categories dominate) - Cache stats via `get_cache_stats` if they ask about performance Present it as a concise summary, not raw JSON. ### Cleanup expired memories 1. Run `get_stats` to show how many memories exist 2. Check if any profiles have TTLs set (this info comes from `list_profiles`) 3. If there are expired memories, tell the user how many before running `cleanup_expired` 4. Run `cleanup_expired` only after confirming with the user -- deletion is permanent ### Export Run `export_profile` with the format the user wants (JSON or Markdown). Tell them where the output goes and how to use it. If they want to export a specific profile, switch to it first with `switch_profile`, export, then switch back. ### Re-embed all memories This is needed after switching embedding
Staff-engineer-level code review delivering 10 prioritized actionable findings across architecture, security, performance, and maintainability
Handle Chainlink CCIP requests including cross-chain token transfers, cross-chain messaging, fund bridging, sender and receiver contract development, message status lookup, route connectivity checks, supported token discovery, and CCT setup. Use this skill whenever the user mentions CCIP, Chainlink cross-chain, cross-chain token bridges on Chainlink, or wants to move tokens or data between blockchains using Chainlink infrastructure, even if they do not say 'CCIP' explicitly.
Fix GitHub issues by analyzing the issue, creating a fix plan, and implementing with user approval. Use when user provides an issue number and asks to fix it, or mentions "fix bug", "bug #", or "issue #".
Guide for uploading local files to Bohrium OSS when MCP tools require file URLs. Use this when you need to transmit local files through MCP tools that cannot accept local paths directly.
LexGuard MCP (한국 법률 MCP 서버) 개발 가이드. 새로운 MCP 툴 추가, Repository/Service 작성, MCP JSON-RPC 엔드포인트 수정, 법령 API 연동, 테스트 작성 시 사용. 아키텍처 패턴, 국가법령정보센터 API 규칙, 응답 형식을 자동으로 준수.
Betting analysis — odds conversion, de-vigging, edge detection, Kelly criterion, arbitrage detection, parlay analysis, and line movement. Pure computation, no API calls. Works with odds from any source: ESPN (American odds), Polymarket (decimal probabilities), Kalshi (integer probabilities).
Deploy the application to staging or production.
Solve problems using knowledge base insights - extracts search terms, runs parallel KB queries, synthesizes advice grounded in your own frameworks
Record implementation pitfalls, debugging insights, and lessons learned into structured devlog documents. Triggers on completing any implementation task that encountered issues, after debugging sessions, after E2E testing, or when user says "record this", "document this pitfall", "add to devlog", "踩坑记录". MUST be invoked after any implementation phase that involved non-trivial bug fixes or workarounds.
Generate synthetic training data variations using image transforms. Increases dataset diversity with flips, brightness jitter, and noise. Use after labeling.
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:
