Skip to main content
The convert-to-overcut skill takes your existing agent or automation framework files and produces Overcut-native artifacts: Skills, Agent specs, and Workflow definitions that import cleanly into an Overcut project. It carries over your SDLC business logic and drops the source framework’s orchestration plumbing. It is the companion to the Overcut API Skill: the converter writes the artifacts, and the API skill imports them into a live project when you are ready.

​
What it converts

The skill recognizes and maps several source frameworks, and falls back to reading intent directly for anything it does not recognize:
  • Argo Workflows and CronWorkflow
  • kagents
  • LangGraph
  • CrewAI
  • AutoGen
  • n8n
  • GitHub Actions
  • Any arbitrary skills or prompts folder
The skill converts business logic, not infrastructure. It keeps what an agent should do, when it should run, in what order, and which capabilities it needs. It drops framework plumbing that Overcut handles for you, such as pod and resource specs, retries and timeouts, state machines, and memory backends.

​
How it works

This is a one-shot batch conversion. You point the skill at your source files, and it produces a reviewable output folder plus a MANIFEST.md that explains every decision.

Inventory the inputs

The skill scans your source directory, detects which framework or frameworks are present, and maps each construct to the Overcut artifact it will become (a Skill, an Agent, a Workflow step, a trigger, or dropped as plumbing).

Distill the business logic

For each construct, it captures the intent in plain language: instructions, roles, quality bars, and step order, separated from the framework that expressed them.

Map to Overcut artifacts

It writes one SKILL.md per skill, one agent spec per persona, and one workflow definition per pipeline. External tool calls (Slack, GitHub, Jira, and others) are mapped to Overcut built-in tools or MCP servers where possible. Anything it cannot map with confidence becomes a flagged TODO rather than a guess.

Emit and validate the output

It writes an out/ folder and runs a validator that checks the JSON parses, every SKILL.md has valid frontmatter, agents carry the required fields, and workflow steps reference real step ids. The output stays importable even where it contains placeholders.

Review, then optionally import

You review the MANIFEST.md: the source-to-target mapping, everything dropped as plumbing, and every open TODO. Nothing is imported automatically.
Required-but-missing fields become explicit placeholders and TODOs, never silent guesses. Review the MANIFEST.md and resolve TODOs (such as unmapped integrations and secrets to create) before you import.

​
Add the skill

You add this skill the same way you add any skill to your agent. The exact steps vary by agent, so check your agent’s documentation. There are two common paths:

Install from the plugin marketplace

If your agent supports plugin marketplaces, add the marketplace repository overcut-ai/overcut-skills and install the overcut-importer plugin.

Or copy the skill folder

Otherwise, clone the overcut-ai/overcut-skills repository and copy the convert-to-overcut skill folder (at plugins/overcut-importer/skills/convert-to-overcut/, including its references/, scripts/, and assets/) into the directory your agent loads SKILL.md skills from.
For example, in Claude Code:
Once installed, ask your agent to convert your framework to Overcut and the skill runs.

​
Import the result

When you are ready to push the converted artifacts into a live project, install the Overcut API Skill as well. The converter hands off to it in this order:
  1. Commit the out/skills/ folders into a repository connected to the project, then create the Skills from those paths.
  2. Create an Agent per generated agent spec, then assign its Skills, MCP servers, and secrets.
  3. Create a Workflow per generated definition. This edits the draft. You review it in the workflow builder and commit it live yourself.
The converter produces artifacts and a plan; it does not design SDLC strategy. Deep product-design questions belong to the built-in Overcut assistant in the web app.