Generate all orchestrator report types — execution summaries, agent performance, workflow analytics, health, config audit, and HTML dashboard with charts. Use after task runs or for project status overview.
What this tool does',
IntelliJ API Power User Guide
Building LLM agents with mlld — tool agents (MCP tools), event-driven agents (routers and dispatchers), and workflow agents (stateless jobs). Use when creating agents, exposing tools, or building event-driven systems.
Analyze pull requests and diffs for bugs, security vulnerabilities, performance issues, style violations, and test coverage gaps — producing structured, actionable feedback
Audit all table and figure captions for language, notation, and formatting consistency
Cybernetics-based multi-agent orchestration for complex tasks. Coordinates a Planner → Generator → Evaluator → Retro pipeline with clean-context sub-agents, per-checkpoint drift prevention, and persistent retro learning.
Creates pages/layouts, defines content collections, configures hydration directives, and wires integrations. Use when adding or modifying Astro pages, layouts, components, or content collections. Trigger terms: Astro, content collection, client:load, client:visible, astro:content
Manage ad campaigns across Google Ads, Meta Ads, LinkedIn Ads, and TikTok Ads. Use when the user wants to analyze campaign performance, research keywords, create campaigns, optimize budgets, or manage ad accounts via the Adspirer MCP server.
Scan, harden, sign, and verify release artifacts with ReleaseGuard — the artifact policy engine for dist/ and release/ outputs.
Update the built-in model configurations for pair-review's AI providers. This skill
Expert guide for using the Local Falcon MCP — an AI-powered local search intelligence platform — to monitor AI visibility (ChatGPT, Gemini, Grok, Google AI Overviews, AI Mode), analyze geo-grid map rankings, evaluate AI sentiment analysis, assess competitor landscapes, and manage Google Business Profile performance. Use this skill whenever the user works with Local Falcon data including: AI search monitoring, scan reports, trend analysis, campaign management, Falcon Guard monitoring, reviews analysis, competitor research, or keyword tracking. Covers metric interpretation (SoLV, SAIV, ARP, ATRP, RVS, RQS), multi-platform analysis across 8 platforms, workflow patterns, credit-conscious scanning strategies, and actionable local SEO and AI search optimization recommendations. Also use when the user asks about AI-powered search presence, local search visibility, map pack rankings, or GBP optimization for any business. --- # Local Falcon MCP Skill ## Overview Local Falcon is an AI-powered local search intelligence platform that monitors business visibility across AI search engines (ChatGPT, Gemini, Grok, Google AI Overviews, AI Mode) and traditional map platforms (Google Maps, Apple Maps), provides AI sentiment analysis via AI-powered scan reports, and delivers deep research review reports. The Local Falcon MCP provides 37 tools for AI visibility monitoring, geo-grid ranking analysis, competitive intelligence, campaign management, GBP monitoring, review analysis, and knowledge base access. The individual tool descriptions explain what each tool does and its parameters. This skill teaches you how to think strategically about Local Falcon data: which tools to combine for common tasks, how to interpret metrics in context, and how to translate raw data into actionable recommendations. Always use the term "Google Business Profile" or "GBP." Never say "Google My Business" or "GMB" — it was rebranded in 2021. ## Core Metrics — Quick Reference ### Ranking Metrics **ARP (Average R
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:
