Personal Statement Writer for Medical Education
Craft compelling personal statements for medical school, residency, fellowship, and graduate school applications in healthcare fields.
When to Use
- - Use this skill when the task needs Use when writing medical school personal statements, residency application essays, fellowship statements, or graduate school admissions essays. Crafts compelling narratives highlighting clinical experiences, research achievements, and career motivations for healthcare education applications.
- Use this skill for academic writing tasks that require explicit assumptions, bounded scope, and a reproducible output format.
- Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.
Key Features
- - Scope-focused workflow aligned to: Use when writing medical school personal statements, residency application essays, fellowship statements, or graduate school admissions essays. Crafts compelling narratives highlighting clinical experiences, research achievements, and career motivations for healthcare education applications.
- Packaged executable path(s):
scripts/main.py. - Reference material available in
references/ for task-specific guidance. - Structured execution path designed to keep outputs consistent and reviewable.
Dependencies
- -
Python: 3.10+. Repository baseline for current packaged skills. - INLINECODE4 :
not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.
Example Usage
CODEBLOCK0
Example run plan:
- 1. Confirm the user input, output path, and any required config values.
- Edit the in-file
CONFIG block or documented parameters if the script uses fixed settings. - Run
python scripts/main.py with the validated inputs. - Review the generated output and return the final artifact with any assumptions called out.
Implementation Details
See ## Workflow above for related details.
- - Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
- Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
- Primary implementation surface:
scripts/main.py. - Reference guidance:
references/ contains supporting rules, prompts, or checklists. - Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
- Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
Quick Check
Use this command to verify that the packaged script entry point can be parsed before deeper execution.
CODEBLOCK1
Audit-Ready Commands
Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.
CODEBLOCK2
Workflow
- 1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
- Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
- Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
- Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
- If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.
Quick Start
CODEBLOCK3
Core Capabilities
1. Structure Generation
CODEBLOCK4
Standard Structure:
- 1. Opening Hook (10-15%) - Captivating patient story or defining moment
- Clinical Experiences (30-40%) - Specific patient encounters with reflection
- Research/Academic (20-25%) - Scholarly contributions and intellectual curiosity
- Service/Leadership (15-20%) - Community impact and teamwork
- Career Goals (10-15%) - Clear vision for future practice
2. Experience Framing
CODEBLOCK5
STAR Method for Experiences:
- - Situation: Brief context
- Task: Your responsibility
- Action: Specific steps you took
- Result: Measurable outcome + personal reflection
3. Character Optimization
CODEBLOCK6
Character Limits by Program:
| Program | Character Limit | Word Approx |
|---|
| AMCAS (Medical School) | 5,300 | ~750 words |
| ERAS (Residency) |
Varies by specialty | ~800 words |
| Fellowship | Usually 1-2 pages | ~1000 words |
| Graduate School | Varies | ~500-1000 words |
4. Tone Adjustment
CODEBLOCK7
Common Patterns
See references/personal-statement-examples.md for:
- - Medical School (MD/DO) Examples
- Residency Personal Statements by Specialty
- Fellowship Application Essays
- Re-applicant Strategies
- Career Changer Narratives
Quality Checklist
Before Writing:
- - [ ] List 3 defining patient experiences
- [ ] Identify unique aspects of your journey
- [ ] Research specific program values
After Writing:
- - [ ] No clichés ("I want to help people", "Since I was young...")
- [ ] Specific examples throughout
- [ ] Personal reflection on every experience
- [ ] Clear connection to chosen specialty
- [ ] Within character limits
- [ ] Proofread for errors
Common Pitfalls
❌ Avoid: "I have always wanted to be a doctor since childhood"
✅ Instead: "My decision to pursue medicine crystallized when..."
❌ Avoid: Listing achievements without reflection
✅ Instead: "This experience taught me..." + specific insight
Skill ID: 203 |
Version: 1.0 |
License: MIT
Output Requirements
Every final response should make these items explicit when they are relevant:
- - Objective or requested deliverable
- Inputs used and assumptions introduced
- Workflow or decision path
- Core result, recommendation, or artifact
- Constraints, risks, caveats, or validation needs
- Unresolved items and next-step checks
Error Handling
- - If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
- If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
- If
scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback. - Do not fabricate files, citations, data, search results, or execution outcomes.
Input Validation
This skill accepts requests that match the documented purpose of personal-statement and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
INLINECODE14 only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
Response Template
Use the following fixed structure for non-trivial requests:
- 1. Objective
- Inputs Received
- Assumptions
- Workflow
- Deliverable
- Risks and Limits
- Next Checks
If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.
医学教育个人陈述撰写者
为医学院、住院医师培训、专科进修及医疗领域研究生申请撰写引人入胜的个人陈述。
使用场景
- - 当任务需要撰写医学院个人陈述、住院医师申请论文、专科进修陈述或研究生院入学论文时使用此技能。能精心构建突出临床经验、研究成果和医疗教育申请职业动机的叙事。
- 适用于需要明确假设、限定范围和可重复输出格式的学术写作任务。
- 当需要为缺失输入、执行错误或部分证据提供有记录的备用方案时使用此技能。
主要特点
- - 以范围为中心的工作流程,适用于:撰写医学院个人陈述、住院医师申请论文、专科进修陈述或研究生院入学论文。能精心构建突出临床经验、研究成果和医疗教育申请职业动机的叙事。
- 打包的可执行路径:scripts/main.py。
- 参考资料位于 references/ 目录,提供任务特定指导。
- 结构化执行路径,确保输出一致且可审查。
依赖项
- - Python:3.10+。当前打包技能的仓库基线。
- 第三方包:此技能包中未明确固定版本。如果此技能需要更严格的环境控制,请添加固定版本。
使用示例
bash
cd 20260318/scientific-skills/Academic Writing/personal-statement
python -m py_compile scripts/main.py
python scripts/main.py --help
示例运行计划:
- 1. 确认用户输入、输出路径及任何必需的配置值。
- 如果脚本使用固定设置,编辑文件内的 CONFIG 块或文档化参数。
- 使用验证后的输入运行 python scripts/main.py。
- 审查生成的输出,并返回最终成果,同时说明所有假设。
实现细节
相关详情请参见上方的 ## 工作流程。
- - 执行模型:验证请求,选择打包的工作流程,生成限定的交付物。
- 输入控制:在运行任何脚本前,确认源文件、范围限制、输出格式和验收标准。
- 主要实现界面:scripts/main.py。
- 参考指南:references/ 包含支持规则、提示或检查清单。
- 需首先明确的参数:输入路径、输出路径、范围过滤器、阈值及任何领域特定约束。
- 输出规范:保持结果可重复,明确标识假设,避免未记录的副作用。
快速检查
在深入执行前,使用此命令验证打包脚本入口点是否可解析。
bash
python -m py_compile scripts/main.py
审计就绪命令
使用这些具体命令进行验证。它们特意保持自包含,避免使用占位符路径。
bash
python -m py_compile scripts/main.py
python scripts/main.py
工作流程
- 1. 在进行详细工作前,确认用户目标、必需输入和不可协商的约束条件。
- 验证请求是否与文档化范围匹配,如果任务需要不支持的假设则提前停止。
- 仅使用实际可用的输入,使用打包脚本路径或文档化的推理路径。
- 返回结构化结果,区分假设、交付物、风险和未解决事项。
- 如果执行失败或输入不完整,切换到备用方案,并准确说明阻止完整完成的原因。
快速入门
python
from scripts.personalstatementwriter import PersonalStatementWriter
writer = PersonalStatementWriter()
生成个人陈述
statement = writer.write(
program
type=medicalschool,
key_experiences=[跟随史密斯医生见习, 免费诊所志愿者, 糖尿病研究],
motivation=帮助服务不足的社区,
character_limit=5300
)
核心能力
1. 结构生成
python
outline = writer.create_outline(
program=residency_surgery,
themes=[领导力, 技术技能, 患者倡导]
)
标准结构:
- 1. 开篇钩子(10-15%)- 引人入胜的患者故事或决定性时刻
- 临床经验(30-40%)- 具体的患者接触经历及反思
- 研究/学术(20-25%)- 学术贡献和求知欲
- 服务/领导力(15-20%)- 社区影响和团队合作
- 职业目标(10-15%)- 对未来实践的清晰愿景
2. 经验框架
python
framed = writer.frame_experience(
experience=在收容所做志愿者,
angle=patient_advocacy,
programtype=familymedicine
)
经验的STAR方法:
- - Situation(情境):简要背景
- Task(任务):你的责任
- Action(行动):你采取的具体步骤
- Result(结果):可衡量的成果 + 个人反思
3. 字符优化
python
optimized = writer.optimize_length(
draft_statement,
target_chars=5300, # AMCAS限制
min_chars=4500
)
各项目字符限制:
| 项目 | 字符限制 | 大致字数 |
|---|
| AMCAS(医学院) | 5,300 | ~750词 |
| ERAS(住院医师) |
因专业而异 | ~800词 |
| 专科进修 | 通常1-2页 | ~1000词 |
| 研究生院 | 因校而异 | ~500-1000词 |
4. 语气调整
python
adjusted = writer.adjust_tone(
statement,
tone=confidentbuthumble,
avoid_cliches=True
)
常见模式
参见 references/personal-statement-examples.md 获取:
- - 医学院(MD/DO)示例
- 按专业分类的住院医师个人陈述
- 专科进修申请论文
- 再次申请者策略
- 转行者叙事
质量检查清单
写作前:
- - [ ] 列出3个关键的患者经历
- [ ] 确定你旅程中的独特之处
- [ ] 研究特定项目的价值观
写作后:
- - [ ] 无陈词滥调(我想帮助别人、从小我就...)
- [ ] 通篇有具体例子
- [ ] 对每个经历都有个人反思
- [ ] 与所选专业有清晰联系
- [ ] 在字符限制内
- [ ] 校对错误
常见陷阱
❌ 避免:我从小就梦想成为医生
✅ 改为:我决定从医的契机是在...
❌ 避免:罗列成就而无反思
✅ 改为:这段经历教会了我... + 具体见解
技能ID:203 |
版本:1.0 |
许可证:MIT
输出要求
每个最终回复应在相关时明确以下内容:
- - 目标或请求的交付物
- 使用的输入和引入的假设
- 工作流程或决策路径
- 核心结果、建议或成果
- 约束条件、风险、注意事项或验证需求
- 未解决事项和后续检查步骤
错误处理
- - 如果缺少必需输入,准确说明哪些字段缺失,并仅请求最少的额外信息。
- 如果任务超出文档化范围,停止执行,而非猜测或悄然扩大任务范围。
- 如果 scripts/main.py 失败,报告失败点,总结仍可安全完成的内容,并提供手动备用方案。
- 不得伪造文件、引用、数据、搜索结果或执行结果。
输入验证
此技能接受与 personal-statement 文档化目的匹配且包含足够上下文以安全完成工作流程的请求。
当请求超出范围、缺少关键输入或需要不支持的假设时,不要继续工作流程。应回复:
personal-statement 仅处理其文档化的工作流程。请提供缺失的必需输入或切换到更合适的技能。
回复模板
对于非简单请求,使用以下固定结构:
- 1. 目标
- 收到的输入
- 假设
- 工作流程
- 交付物
- 风险和限制
- 后续检查
如果请求简单,可以压缩结构,但当假设和限制影响正确性时,仍需明确说明。