Community-maintained Agent Skills for TRAE.
- Clone this repository.
- Put skills into the right location for TRAE:
- Project skills:
.trae/skills/<skill-name>/SKILL.md - Global skills:
~/.trae/skills/<skill-name>/SKILL.md
- Project skills:
- Refresh TRAE's skill discovery in settings (location varies by TRAE version).
- Ask TRAE for a task that matches a skill’s description, for example:
- “Use the git-commit-generator skill to draft a commit message for the current changes.”
- “Use the cn-punctuation-checker skill to check Chinese punctuation in this document.”
Agent Skills are folders of instructions, scripts, and resources that an AI agent can discover and load dynamically to perform specialized tasks in a repeatable way. A typical skill is a directory with a SKILL.md file that contains:
- YAML frontmatter metadata (especially
nameanddescription) - A Markdown body with steps, guidelines, and examples
This pattern keeps the agent’s core rules lightweight while making SOP-style workflows portable and shareable.
- Skills vs. Rules: rules are fully injected into every chat and continuously occupy context; skills are loaded on-demand only when called.
- Skills vs. MCP servers: skills describe how TRAE should accomplish a task; MCP servers provide tools that TRAE can call. For example, a Playwright MCP server provides browser automation tools, while a testing skill defines test structure, conventions, and execution workflow.
- Global skills: reusable across projects (personal/team conventions, general toolchain workflows, long-term output preferences).
- Project skills: apply only to the current project (project-specific business rules, architecture constraints, project scaffolding/testing workflows).
This repository is intended to follow a simple, discoverable layout:
skills/
_template/ # Template for creating new skills
SKILL.md
<skill-name>/
SKILL.md # (Mandatory) Core instructions for the agent
(optional) examples/ # Input/output examples
input.md
output.md
(optional) templates/ # Reusable templates
component.tsx
(optional) resources/ # Reference files, scripts, or assets
style-guide.md
To create a skill, start with the skill template and follow the contributing guide.
| Skill | Description | Usage Scenario | Status |
|---|---|---|---|
| daily-trend-writer | Automated WeChat Official Account content production pipeline. Daily discovers "small but beautiful" topics like practical tools, community hotspots, tutorials, then generates two high-quality articles: "Mimeng-style" and "technical deep-dive". | Content Creation, WeChat Official Account, Trend Analysis | Stable |
| git-commit-generator | Generate standardized git commit messages based on code changes (diffs), following Conventional Commits specification. | Git Operations, Code Review | Stable |
| cn-punctuation-checker | Checks Chinese text for incorrect English punctuation marks and supports batch fixing. | Chinese Copy Editing, Punctuation Correction | Stable |
| wechat-mini-program-development | WeChat mini-program development skill with standard project structure, request wrapper, and API management. | WeChat Mini-Program Development, Project Scaffolding | Stable |
| kz-article-deep-analysis | Deeply interpret non-academic articles (blogs, essays, commentary) and output a structured analysis report (core issue, thesis, argument map, cognitive gains). | Reading, Article Analysis | Stable |
| video-to-keyframes | Extracts video frames, detects cuts/segments, selects candidate keyframes, and generates review HTML galleries. | Video Analysis, Keyframe Selection, Storyboard Screening | Stable |
| web-design-teroop | Comprehensive design guidance for new frontend projects, covering style, logos, icons, and animations. | New Project, Web Design, UI/UX, Branding | Stable |
| trae-claw-install | Repository-driven OpenClaw deployment workflow with platform routing, acceptance checks, and unified troubleshooting steps. | OpenClaw Deployment, DevOps Workflow, Troubleshooting | Stable |
| cloudbase | Tencent CloudBase development in Trae — MCP-first workflow for Web, WeChat Mini Program, auth, databases, cloud functions, CloudRun, storage, and built-in AI. | CloudBase, 腾讯云开发, Web, Mini Program, Serverless | Stable |
| project-governance | Project governance workspace for AI-assisted development — project protocol (rules, permissions, autonomy levels), directory index, lessons log, session handoff, changelog, version index, and whitelist/blacklist parameter registries, with a scaffold/validate/index/check CLI. | Project Setup, AI Agent Onboarding, Parameter Versioning, Project Governance | Stable |
| cycle-delivery | Evidence-gated software delivery through a local MCP control plane: immutable request, blind reviews, arbiter approval and exact-byte Git delivery. Requires the trae-cycle binary from the project GitHub release. | Software Delivery, Code Review, Governance, Git | Stable |
| gbr-pair | Pair a phone running Build Remote Agent to this Trae session (gbr/1). Attach only loopback Bot API :8788 or gbr-mcp stdio. Phone is spectator. |
Mobile spectator, pairing, MCP | Stable |
| docx-diff-comment | Compare two Word documents to find new features in V2, add comments to the V2 document for each new feature, and generate a requirements table with effort estimation in person-days. | Document Comparison, Word Comments, Requirements Estimation | Stable |
See CONTRIBUTING.md.
See LICENSE.
Skills in this repository are provided for community/educational use. Always review and test skills in your own environment before relying on them for production or security-sensitive workflows.
- TRAE website: https://www.trae.ai/
- TRAE Skills docs: https://docs.trae.ai/ide/skills?_lang=en