Introduction
Most people using AI coding tools are prompting and praying. Type, hope the output works, start over when it doesn’t. The feature that actually changes how AI agents write code for you — and that almost nobody sets up properly — is skills: small, named, reusable workflows your agent looks up dynamically and runs the same way every time.
This guide walks through what skills are, how they’re different from prompts and rules, and how to build them inside Trae Solo (the new desktop app from the Trae team) — with patterns that transfer cleanly to Claude Code, Cursor, Codex, and any other agent that supports skills. By the end you’ll have a working backend-conventions skill, an API-testing skill that auto-runs after every endpoint change, and a research skill that produces a daily briefing.
📚 Table of contents
- What a skill actually is
- Why skills beat long prompts and bloated context
- Trae Solo at a glance — MTC vs Code mode
- Installing a skill from the marketplace
- Building your own skill in three ways
- Worked example: FastAPI backend conventions skill
- Worked example: auto-test API skill
- Worked example: daily research briefing skill
- Skills vs rules vs MCP servers
- Best practices
- Common mistakes
- Frequently asked questions
📜 What a skill is
A skill is a folder containing a single required file — SKILL.md
— plus any supporting files (scripts, examples, templates) it needs. The
SKILL.md declares a name and a
one-line description; the body explains how to do the task and references the supporting files.
The two-tier loading model
- The agent always sees: skill name + description (a few tokens each)
- The agent loads the full body only when it decides to use the skill
- You can ship 50 skills without bloating context
- Inside the body, you can reference other files for further depth
🎯 Why skills beat long prompts
Long prompts
- You retype the same instructions
- Variations creep in across sessions
- Context window fills up fast
- Hard to share with teammates
Skills
- Write once, reuse infinitely
- Same instructions every time — consistency
- Loaded only when needed — lower context
- Live in the repo — share via git
🚀 Trae Solo at a glance
Trae Solo is the new free desktop/web app from the Trae team. Two operating modes:
MTC mode (More Than Coding)
General-purpose agent: research, summarization, office tasks. Supports skills, web search, and cross-tool workflows.
Code mode
Natural-language full-stack development with live preview. Selectable elements, multi-task execution, a file manager built in.
Skills live in .trae/skills/<skill-name>/
per project. Trae auto-loads the skill index for every session and dynamically pulls in
SKILL.md when needed.
🛒 Installing a skill from the marketplace
Easiest entry point. Open the Skills tab, browse pre-built skills (UI design, brand guidelines, etc.),
click install. The skill shows up in your project, loadable with /
in any chat: type /front-end-skill
and it’s in the conversation context.
🛠️ Building your own skill
Three ways:
- Upload a local skill. Drop a
SKILL.mdfrom another project. - Install from marketplace. Pick from community-built skills.
- Ask Trae to generate it. Describe what you want; reference the skill-format docs; let the agent author the file.
The third path is the highest leverage. Modern models reliably produce well-shaped
SKILL.md files when you point them at
the spec.
🧱 Example 1 — FastAPI backend conventions
Prompt
“Create a local project skill called fastapi-backend.
Use any time backend work is done. Conventions: separate API routes per category (auth, users, db,
etc.), short comments only, single-sentence docstrings only when needed. Follow the [link to Trae
skill docs] format.”
Trae creates the skill folder with a SKILL.md
that encodes those rules. Any future prompt that mentions FastAPI auto-loads the skill and produces
consistent output. Iterate on the skill over time as you find sharper rules.
🧪 Example 2 — auto-test API skill
Prompt
“Create a test-api skill. Any
time an endpoint is added or changed, run curl requests covering all cases, then produce a report
with requests, responses, working/broken status, and one suggestion per issue. Full coverage on
every change.”
Now after building any new route, prompt “run the test-api skill” (or just let Trae invoke it automatically). You get a structured QA report without writing test code yourself. Use it as a feedback loop before merging anything.
📰 Example 3 — daily research briefing
Skills aren’t coding-only. In MTC mode, build skills for repeatable knowledge work.
Prompt
“Create a daily research skill. Search trending AI topics, tools, news, investment. Output a bulleted summary under 250 words plus one YouTube video title idea, tailored to a large coding/AI channel. Markdown output. Pull from any web source.”
Trae generates a skill with both a SKILL.md
and supporting example files. Run it every morning, or schedule it via the agent. As you iterate,
refine the output format and the skill keeps improving.
🆚 Skills vs rules vs MCP servers
Three patterns, easy to confuse. Use each for what it’s good at.
Skills
Dynamically loaded when the agent decides it’s relevant. For repeatable workflows.
Rules
Loaded into context on every session. For absolute conventions that must always hold.
MCP servers
Expose tools (functions) to the agent. A skill can describe how to use those tools.
Powerful combo: an MCP server gives access to a tool, a skill describes the right way to use it, a rule enforces non-negotiables like “never write secrets to logs.”
✅ Best practices
- One-line description that the agent can match on. Be specific.
- Reference external files for examples rather than inlining 500 lines.
- Iterate — treat skills as living docs you tune over weeks.
- Commit skills to git so the whole team benefits.
- Build a skill the moment you find yourself doing something for the third time.
- Use skills to document tricky tool usage (especially poorly-documented MCPs).
- Keep rules small and skills numerous — flexibility lives in skills.
❌ Common mistakes
- Vague descriptions that don’t trigger when relevant
- Mega-skills that try to do five jobs — split them up
- Pasting a skill body that contradicts the project’s rules
- Using skills for things that should be rules (absolute conventions)
- Forgetting to commit skills — teammates don’t get them
- Skipping examples in the skill body — the agent has nothing to anchor on
- Treating skills as set-and-forget — they need iteration
Conclusion
Skills are the productivity primitive most AI-coding users don’t use yet. Once you set up three or four for the patterns you repeat — backend conventions, testing, code review, daily research — the agent stops feeling like a stranger you re-onboard every session. It feels like a teammate who knows how your project does things.
Trae Solo makes the loop tight: marketplace install, agent-authored skills, MTC and Code modes in one app, free to use. The pattern transfers to Claude Code, Cursor, Codex, and any agent that supports skills. Start with one. Watch what changes.
Related reading: Claude Code advanced MCP and skills setup — Claude Code hands-on deep dive — Claude AI review
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