Methodology Skills for AI Agents
A methodology skill packages a human method into repeatable agent instructions: when to use it, when not to use it, the steps to follow, and the quality checks that keep the output honest.
Why it matters
Most teams do not only need a smarter model. They need the model to follow known ways of thinking: root-cause analysis, structured writing, goal setting, decision scoring, or continuous improvement. A methodology skill turns those methods into repeatable agent behavior without asking the user to rewrite the method every time.
Pick a method
- 01Need a clear recommendation?Pyramid Principle
- 02Need root cause?5 Whys
- 03Need a measurable goal?SMART or OKR
- 04Need repeated improvement?PDCA
- 05Need options compared?Decision Matrix
Practical checklist
- Name the method and the kind of task it fits
- State when not to use the method
- Break the method into ordered steps
- Add quality questions that can reject weak output
- Include a small example input and output
- Keep human review for high-stakes decisions
Example
A 5 Whys skill does not just say “find the root cause.” It starts from one concrete failure, asks why with evidence, stops when the cause is actionable, then adds a validation check so the fix can be reviewed.
Common failure modes
Related templates
FAQ
No. A prompt can ask for one answer. A skill makes the method reusable by including fit, steps, validation, examples, and failure conditions.