| name | CV Polish |
| description | This skill should be used when the user asks to "polish my CV", "improve my CV", "tailor my CV", "optimize my resume", or runs /ra:cv-polish. It improves CV content, structure, and wording for specific applications. |
CV Polish Skill
Prerequisite Check
Read the file ${CLAUDE_PLUGIN_ROOT}/.local.md at the start of this skill. If cv_profile_analyzed is not true or the ## CV Profile section is empty, output:
未检测到 CV 画像。 请先运行 /ra:cv-analyze 分析你的 CV，其他功能依赖 CV 画像数据。
Output this message and stop immediately.
Personalization Mode
Before proceeding with analysis, ask the user:
是否需要个性化定制？会问你 4-5 个问题来生成更贴合你需求的结果。
If the user declines personalization, proceed with the standard flow using existing .local.md data.
If the user accepts personalization, ask the following 4-5 targeted questions (use AskUserQuestion for each):
- Target degree type and school? (e.g., "PhD in Computer Science at MIT")
- Which 1-2 experiences do you want to highlight most?
- Is there a specific research direction you want to align with?
- What is your preferred CV language? (e.g., English, Chinese, bilingual)
Standard Flow
Step 1: Locate and Read the CV File
- Check
.local.md for the user's CV file path (look in the CV Profile section).
- If no path is specified, ask the user for the CV file path.
- Read the CV file using the Read tool.
Step 2: Analyze the CV
Analyze the CV across the following dimensions:
- Structure: Is the organization logical? Are sections in the right order for a research application? Standard order: Education, Research Experience, Publications, Skills, Awards, Teaching, Other.
- Wording: Are bullet points action-oriented and results-driven? Are there weak verbs, passive voice, or vague descriptions?
- Emphasis: Are the most relevant experiences and skills given the most prominent placement? Does the CV highlight research-relevant accomplishments?
- Missing Elements: Are there categories important for research applications that are absent or underdeveloped? (e.g., research statement keywords, technical skills, publications, presentations)
- Formatting Consistency: Are dates, locations, and formatting uniform throughout?
- Length: Is the CV appropriately concise? (Typically 1-2 pages for a master's application, 2-3 pages for a PhD application)
Step 3: Determine Edit Mode
Ask the user how they would like to receive the improvements:
I've identified several areas for improvement. Would you prefer:
- Line-by-line suggestions that you apply yourself
- Direct edits to the file with tracked changes explanation
Proceed according to the user's choice.
Step 4: Apply Improvements
If tailoring for a specific position or school:
- Reframe bullet points to emphasize skills and experiences relevant to the target program
- Reorder sections to prioritize the most relevant information
- Add missing keywords that align with the target program's research focus
- Adjust the research interest statement to match the target department's strengths
- Highlight relevant coursework, tools, or methodologies
General improvements to apply:
- Replace weak verbs (e.g., "helped with", "worked on") with strong action verbs (e.g., "developed", "designed", "implemented", "analyzed")
- Quantify achievements where possible (e.g., "improved accuracy by 15%")
- Ensure each bullet point communicates a clear contribution or outcome
- Standardize date formats and section headings
- Remove irrelevant or redundant information
Step 5: Output Results
Provide the user with:
- A summary of all changes made, organized by category (structure, wording, emphasis, additions, removals)
- The improved CV (either as inline suggestions or as a directly edited file)
- A brief explanation of why each change improves the CV for research applications
If the user provided a specific target, also include a brief note on how the CV was tailored for that target and any remaining gaps the user should address in their research statement or other application materials.
