Global intelligence hub. Three-sector architecture (Politics/Finance/Tech) with cross-sector causal chain analysis, market anomaly detection, and delta engine. Collects from Google News, Yahoo Finance, RSS, Hacker News, and search engines.
Help integrate Grip Connect in web, Capacitor, React Native, runtime, and CLI projects. Use for package selection, supported device setup, Bluetooth constraints, streaming and export workflows, CLI and runtime usage, connection troubleshooting, and unsupported custom device guidance. --- # Grip Connect Use this skill when a user is building with Grip Connect packages, choosing a platform, wiring a supported device, or debugging connection and setup issues. ## Start with platform and device
General conventions when creating an application design
Communicate with remote agents via A2A protocol, discover available agents, and ask the human owner for clarification via the A2A Hub. Use when asked to send messages to other agents, discover what agents are available, or when you need human input to proceed. **Triggers — use this skill when:** - You need human input to proceed (approval, decision, clarification) - User asks to "send a message to another agent" - User asks to "discover agents" or "what agents are available" - You're stuck and need to escalate to the owner - A long-running task needs human approval before continuing --- # A2A — Agent-to-Agent Communication & Human-in-the-Loop ## Tools | Tool | Purpose | |------|---------| | `a2a_discover` | Find remote agents on the hub or static registry | | `a2a_send` | Send a message to a remote agent by name, ID, or URL | | `ask_owner` | Ask the human owner a question (non-blocking) | --- ## ask_owner — Human-in-the-Loop Use `ask_owner` when you **genuinely cannot proceed** without human input. The tool submits your question to the hub and **returns immediately** — it does NOT block your session. When the owner responds, a **fresh pi subprocess** is automatically spawned with your handoff context + the owner's answer to continue the work. ### How It Works 1. You call `ask_owner` with a question + handoff context 2. The question is submitted to the A2A Hub — you get an immediate confirmation 3. You continue with other work or end your session 4. The owner answers through the hub's web UI (could be minutes or hours later) 5. A background poller detects the response 6. A fresh `pi` subprocess is spawned with a self-contained prompt containing: - The original question - The owner's response - Your full handoff context (done, remaining, decisions, etc.) 7. The new session picks up where you left off — no prior conversation context needed ### When to Use - **Approval needed** — destructive operations, merging PRs, deploying - **Ambiguous requirements** — multiple vali
>-
End-to-end checklist for delivering new capabilities across CLI, presets, and tests
Use when building any system where email content triggers actions — AI agent inboxes, automated support handlers, email-to-task pipelines, or any workflow processing untrusted inbound email. Always use this skill when the user wants to receive emails and act on them programmatically, even if they don't mention "agent" — the skill contains critical security patterns (sender allowlists, content filtering, sandboxed processing) that prevent untrusted email from controlling your system.
This skill SHOULD be used when the user asks to "review code", "find dead code", "check for duplication", "simplify the codebase", "find refactoring opportunities", "do code cleanup", "check naming consistency", "analyze test organization", "run codebase health check", "review my PR", "refactor this code", "extract method", "rename variable", "consolidate duplicates", "adversarial review", "red team review", "find ways to break this", "multi-model review", "get multiple AI opinions on this code", "hunt bugs", "find bugs", "bug hunt", or "adversarial bug hunt". Routes to specialized analysis agents, refactoring workflow, multi-model adversarial review, or adversarial bug hunt based on the type of request.
Add "Open in molab" badge(s) linking to marimo notebooks. Works with READMEs, docs, websites, or any markdown/HTML target.
Google Ads account audit and business context setup. Run this first — it gathers business information, analyzes account health, and saves context that all other ads skills reuse. Trigger on "audit my ads", "ads audit", "set up my ads", "onboard", "account overview", "how's my account", "ads health check", "what should I fix in my ads", or when the user is new to AdsAgent and hasn't run an audit before. Also trigger proactively when other ads skills detect that business-context.json is missing.
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
Use SwarmVault when the user needs a local-first knowledge vault that writes durable markdown, graph, search, dashboard, review, and MCP artifacts to disk from books, notes, transcripts, exports, datasets, slide decks, files, URLs, code, and recurring source workflows.
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:
