Build your own workflow

Summary

Covers automating the SDD workflow with Agent Skills, transitioning from MCP servers to CLI-based skills, and using community tools like Spec Kit and OpenSpec. Also introduces research backlogs for mid-feature ideas.

Key Takeaways

• Agent Skills automate repeatable prompts: package frequently-used prompts (like feature spec generation) into reusable skills
• MCP to CLI + Skills trend: CLI tools with skills are increasingly replacing MCP servers for lower setup cost and less context usage
• Community tools extend SDD: Spec Kit and OpenSpec provide pre-built SDD workflows; plugins add new capabilities to agents

视频信息：Build your own workflow

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English Script

You’ve now mastered an SDD workflow. Want something faster and lightweight? In this lesson, we will automate things but doing it our way with a custom process. We previously showed Agent Skills, an open standard to give agents new capabilities and expertise. For example, we repeat the same prompt when starting a feature spec. Do this, do that, write these three files. Let’s automate this with a skill and with help from the agent to write it. Ask the agent to use its skill creator to talk through this with us. As a note, there are many of these skill skills in the community that you can also install and use. As the agent runs, it might ask some follow-up questions. These are usually quite good. When the interview is done, we submit the responses and the agent proceeds. While the agent is working on the skill, keep an eye on the output. Is it making the choices you wanted? Success. As you can see, the agent wrote the skill to this directory. As a note, skills can be per project or global.

Skills can be invoked in several ways. In your prompt, refer to the skill before saying what to do. Also, you can ask the agent to call a skill from another skill. According to the skills open standard, agents use the skill description to decide when to call it in a process called progressive disclosure. But their judgment isn’t always perfect, especially as the context window gets larger. Use the same heuristic as file tagging. If you know you want a skill used, name it. That saves you some thinking tokens. Agents have built-in / commands like /clear. Though initially popular, many agents are moving from custom/commands over to skills.

Sometimes you need to give the agent more resources like access to some API, a private knowledge base, database, and so on. Until now the universal way to extend an agent has been MCP, Model Context Protocol. For example, agents need current quality context about packages. The most popular choice, Context7, an MCP that brings updated documentation of packages into your agent context. Now your agent can stay up to date with React 9.2 and higher instead of React 9.0. MCP servers are still popular, but skills that use code tools like a CLI, command line interface, often accomplish the same purpose more elegantly. Context7 now suggests this, a skill that calls a CLI tool for Context7. Let’s install the Context7 package for Claude Code. During the setup, we see this immediately. A choice between MCP server and CLI + Skills. We’ll use the second choice. If this is your first time, you’ll need to make an account. We already did so and logged in. Once done, we can go back into Claude Code and put it to use with an example prompt that uses Context7. As the agent runs, we see it detects the need to use Context7. When it completes, the agent shows it now knows how to find out information about our tech stack. This trend from MCP servers to skills plus CLI is accelerating. People are rethinking MCP because CLI tools can take action with less setup and less context usage.

As you scale your workflow implementation, skills, etc. You will want to share it with yourself, across machines, with teammates, perhaps with the outside world. Some agents such as Claude Code have plugins, a collection of agent extensions that can be installed and updated. There’s a growing community of free plugins. Check them out to see if any will boost your SDD productivity. Remember, plugins are not yet a cross-agent standard. Like apps or dependencies, plugins can execute code, so make sure you trust them on install and update. GitHub’s Spec Kit is one attempt at formalizing a spec-driven development workflow with agents. Installing Spec Kit for a project gives you access to / commands in your agent, similar to the workflow you used in this course. spec-kit constitution, plan, tasks, and implement. Another popular alternative is OpenSpec from Fission AI. OpenSpec follows a similar propose, explore, apply, archive workflow, where propose and explore match with the plan step, apply matches with implement, and archive matches with replanning. It also has canonical patterns for quick features. Both packages include helpful features like branch management, verification scripts, and opinionated spec document formats. I encourage you to experiment with these open source workflows to help refine your own.

Sometimes in the middle of a feature, you have an idea. You want to research it with the agent, but you don’t want to stop your branch work. For example, a choice of databases. But you’re not yet committed to this idea, so you don’t want it on the roadmap. The conversation produces some good ideas and some good questions. We accept most of the recommendations, but change our mind on one of them. You don’t want to lose it. So, let’s keep a backlog of research by telling the agent to write a report in a well-known location. This file is a record of your conversation and results. You can later ask the agent to schedule this research on the roadmap with a link to the backlog file. As this grows, you can write a skill to automate your research. Spec-Driven Development helps the agent write code your way. You can adopt an existing SDD framework or tool, then customize it using skills to operate your projects with your team, your way.