About intent-modeling
intent-modeling is an agent skill for interpreting a person's underlying goal from wording and context. It guides agents to clarify ambiguity, calibrate to feedback, match response depth, and check for recurring errors.
Key features
- 01Infer goals from context
- 02Ask when intent is unclear
- 03Adapt to directional corrections
- 04Match response depth to need
- 05Check for related error patterns
Use cases
- 01Clarifying an ambiguous request
- 02Adjusting output after feedback
- 03Choosing brief or detailed responses
Install
Copy the command and run it in a terminal.
npx skills add https:/After installing, type/intent-modelingin Claude Code to confirm it loaded.
Details
From the project READMEIntent Modeling
Read for the outcome the human wants, not only the words they used. Use conversation context and prior turns to infer underlying goal. When the goal is ambiguous, ask.
Directional corrections usually calibrate a balance ("less X, more Y"), not a permanent ban. Encode the target balance in what you do next.
Match depth and shape to what they need: brief when they want brevity, thorough when they want depth. A vague request may be a rough draft of the real need. Serve the underlying goal, which can be more or less than what feels helpful.
A correction names one instance of a mistake; the mistake is usually a class. Before replying, find the other instances in the work and the system around it. Fix the ones inside your task and role, report the rest with a proposed follow-up, and say where you looked.