Create and update ai-context.md files that document modules for AI assistants. Use when adding documentation for packages, apps, or external references that should be discoverable via /modules commands.
Build Bifrost workflows, forms, and apps. Use when user wants to create, debug, or modify Bifrost artifacts. Supports SDK-first (local dev + git) and MCP-only modes.
Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations. Supports dashboard creation, updates, data extraction, structure analysis, and best practices.
Work effectively in PTO-ISA: choose the right backend, run CPU/SIM/NPU flows, trace instruction constraints, understand A2/A3 vs A5 differences, align with PTO-AS, and debug failures.
Use when preparing commit messages, pull request titles, or summary comments for this repository. Enforce `type(scope): subject` without `[codex]`, using one of `feat`, `fix`, `test`, `chore`, or `docs`.
Personal network intelligence — remember people, find connections, and draft intros. Contacts stored locally as plain markdown files.
Create a well-formed git commit from current changes using session history for rationale and summary; use when asked to commit, prepare a commit message, or finalize staged work. --- # Commit ## Goals - Produce a commit that reflects the actual code changes and the session context. - Follow common git conventions (type prefix, short subject, wrapped body). - Include both summary and rationale in the body. ## Inputs - Codex session history for intent and rationale. - `git status`, `git diff`, and `git diff --staged` for actual changes. - Repo-specific commit conventions if documented. ## Steps 1. Read session history to identify scope, intent, and rationale. 2. Inspect the working tree and staged changes (`git status`, `git diff`, `git diff --staged`). 3. Stage intended changes, including new files (`git add -A`) after confirming scope. 4. Sanity-check newly added files; if anything looks random or likely ignored (build artifacts, logs, temp files), flag it to the user before committing. 5. If staging is incomplete or includes unrelated files, fix the index or ask for confirmation. 6. Choose a conventional type and optional scope that match the change (e.g., `feat(scope): ...`, `fix(scope): ...`, `refactor(scope): ...`). 7. Write a subject line in imperative mood, <= 72 characters, no trailing period. 8. Write a body that includes: - Summary of key changes (what changed). - Rationale and trade-offs (why it changed). - Tests or validation run (or explicit note if not run). 9. Append a `Co-authored-by` trailer for Codex using `Codex <[email protected]>` unless the user explicitly requests a different identity. 10. Wrap body lines at 72 characters. 11. Create the commit message with a here-doc or temp file and use `git commit -F <file>` so newlines are literal (avoid `-m` with `\n`). 12. Commit only when the message matches the staged changes: if the staged diff includes unrelated files or the message describes work that isn't staged, fix the index or revise the message
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
Designs agent-native applications where agents are first-class citizens with full tool parity, atomic primitives, and explicit completion signals. Covers tool design, context injection, agent-to-UI communication, and mobile checkpoint/resume patterns. Use when architecting an agentic system, designing tool surfaces, building agent-aware UI, implementing context.md patterns, or asking "how do I make my app agent-native.
中国平台深度研究引擎 - 覆盖微博、小红书、B站、知乎、抖音、微信公众号、百度搜索、今日头条等8大平台，AI综合分析生成有据可查的研究报告。
A股短线分析助手，聚焦“短线交易信号 + 营收质量”双轨研判。默认采用 Team-First 并行分析，主数据源为 Web Search，东方财富仅做结构化补充与复核。
Write Yo async code and algebraic effect handlers. Use this when working with IO, Future, JoinHandle, using/given, io.async, io.await, io.spawn, return, and escape.
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:
