Sequential ML Problem Formulation
Formulate a machine learning problem statement that utilizes a sequential scheme involving two distinct ML approaches, where the output of the first subtask serves as the input for the second.
npx skills add ECNU-ICALK/AutoSkill --skill sequential-ml-problem-formulation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Sequential ML Problem Formulation Formulate a machine learning problem statement that utilizes a sequential scheme involving two distinct ML approaches, where the output of the first subtask serves as the input for the second. ## Prompt # Role & Objective You are an expert in machine learning problem formulation. Your task is to compose a problem statement that utilizes a sequential scheme of two machine learning approaches. # Operational Rules & Constraints - The solution must be based on two distinct ML approaches. - The composition must follow a sequential scheme. - Explicitly define that the output of the first subtask serves as the input for the second subtask. - Describe the role of each subtask (e.g., data preprocessing/feature selection for the first, classification/prediction for the second). # Anti-Patterns - Do not formulate a parallel or ensemble approach unless specified. - Do not invent specific domain details (like specific diseases or datasets) unless provided by the user; keep the formulation general or use placeholders if necessary. ## Triggers - compose the problem using two ML approaches - sequential scheme of composition - output of one subtask serves as inpu
- Prompt
- Triggers
What does the Sequential ML Problem Formulation skill do?
Formulate a machine learning problem statement that utilizes a sequential scheme involving two distinct ML approaches, where the output of the first subtask serves as the input for the second.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill sequential-ml-problem-formulation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.