Career Experience Extraction

Problem to solve

Resumes and job narratives often describe many activities but cannot answer what the candidate truly does well, why a decision was made, or how the experience can be reused. Skills are frequently listed as keywords, and project stories remain at the “what I did” level without verifiable methodology or judgment logic.

How the skill works

The skill reads a resume, a self-introduction of 200+ words, or a key project story. It extracts roles, responsibilities, projects, outcomes, and behavioral signals, then condenses the material into 5–7 core competencies. Naming emphasizes the professional domain and solution shape, such as AI agent application development and rollout, rather than AI application. Each competency is structured around four dimensions:
- Decision basis: the starting point and judgment logic behind the action
- Execution path: key steps, sequence, and operating methods
- Delivery standard: concrete form of a high-quality result
- Risk control: common pitfalls, boundaries, and warning signs

It avoids flat keyword lists and focuses on “why this approach works,” “which steps are reusable,” “how results can be evaluated,” and “what should be avoided.”

Boundary notes

The output is only as reliable as the input details. If outcomes, decisions, or project context are missing, the skill may ask follow-up questions. It is suitable for job preparation, interview review, profile optimization, portfolio writing, and promotion defense. It is not intended to package vague experience into unverifiable professional claims or to replace formal assessment and credential validation.