cv-polish

name	cv-polish
description	Use when the user asks to polish a CV or resume, improve a CV, tailor a resume, or optimize a CV. Based on the shared application profile, suggest revisions or produce rewrites for structure, phrasing, and target-program fit.

CV Refinement

Preconditions

• Read ../../memory.md first.
• If cv_profile_analyzed is not true, or ## CV Profile is basically empty, first suggest that the user run cv-analyze, unless the user explicitly asks you to rebuild the profile directly from the current CV.

Language Rules

• Support three output modes: zh, en, and bilingual.
• If the user explicitly specifies the output language or target CV language, prioritize the user's specification.
• Otherwise read preferred_language from memory.md.
• If it is still unclear, default to following the user's current conversation language.
• If the user requests bilingual output, prioritize one main version plus a short counterpart note, rather than mechanically repeating every line twice.

Fill In the Key Information First

If any of the following is missing, ask concise questions in Chinese to fill it in:

• target program / school / degree
• which 1 to 2 experiences should be emphasized
• target research direction
• desired output language

Working Method

1. Read the original CV:
   • Prefer the cv_file_path recorded in memory.md
   • If it is missing, then confirm the path with the user
2. Review it from the following dimensions:
   • whether the structural order fits research-oriented applications
   • whether the bullets use clear verbs and explicit outcomes
   • whether research-related experience is placed early enough
   • whether common research-application elements are missing, such as publications, research experience, methods, or technical stack
3. Make targeted refinements based on the target program:
   • strengthen the experiences most relevant to the target direction
   • adjust section order
   • add necessary keywords, but do not invent experiences
4. Decide the delivery mode based on the source file type:
   • if it is a text-based source file, it can be edited directly
   • if it is a format such as PDF / DOCX that is not suitable for stable direct rewriting, default to section-by-section rewriting suggestions and a copyable new version

Output Requirements

• Include at least three parts:
  • the main issue list
  • the refined version or section-by-section rewriting suggestions
  • why these changes fit research applications better

Constraints

• Do not force ordinary industry experience into fake research experience.
• Do not delete hard information that is valuable for application judgment just for appearance.
• If the user has given a clear target, prioritize that target instead of doing generic CV optimization.