Manage context-mode GitHub issues, PRs, releases, and marketing with parallel subagent army. Orchestrates 10-20 dynamic agents per task. Use when triaging issues, reviewing PRs, releasing versions, writing LinkedIn posts, announcing releases, fixing bugs, merging contributions, validating ENV vars, testing adapters, or syncing branches.
Given a GitHub issue number, plan and implement the work described in the issue. Operates iteratively - creates an implementation plan, responds to feedback, and only builds when the 'state:agent-ready' label is applied. Includes tests, documentation updates, and PR creation. Trigger keywords - build from issue, implement issue, work on issue, build issue, start issue.
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.
Think before building. Use when the user asks to reason about, analyze, evaluate, compare options, make an architecture decision, choose between approaches, think through a problem, or assess trade-offs. Also use when the user asks 'why did we...', 'should we...', 'what are our options', 'is this the right approach', or wants to frame/reframe a problem.
Consult Codex as an independent expert. Sends a question or task to codex exec and returns the response.
Manage GitHub issues locally as Markdown files. Use for triaging, searching, editing, and creating issues without leaving your editor or terminal.
Answer a question about a GRACE project using full project context. Use when the user has a question about the codebase, architecture, modules, or implementation — loads all GRACE artifacts, navigates the knowledge graph, and provides a grounded answer with citations.
Review code for bugs, style issues, and improvement opportunities
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 #".
Convene a panel of CLI-based AI agents (Codex, Gemini) to deliberate on a question. Each agent answers independently, then you synthesize the council's verdict as chairman. Use for architecture decisions, code review, debugging hypotheses, or any question where diverse perspectives add value.
Create a GitHub issue in nerdai/llm-agents-from-scratch and add it to project #11. Use when asked to create a ticket, issue, or task. Supports labels and issue kinds like book-diagrams.
This skill should be used when the user asks to "run acli jira commands", "create a Jira issue", "search Jira issues", "manage Jira projects", "transition Jira status", "check jira issue", "consistent with jira issue", or mentions ACLI, Atlassian CLI, Jira CLI, Jira issue keys (e.g. KAN-1, PROJ-123), or jira workitem/project/board/sprint operations via the command line.
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:
