Format CVs for academic positions with publications, grants, and teaching
日本語の概要は準備中です。原文の説明を表示しています。
Determines the candidate's primary role identity before any JD analysis. Classifies into role families, selects core tech identity, ranks projects by role relevance, and outputs a Candidate Position Brief consumed by all downstream stages. This is Phase -1 of the pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
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Use this skill as Phase -1 — the very first step — before JD analysis, before bullet generation, before anything. This skill answers the most important question:
"What kind of candidate are you?"
Trigger phrases: "position me for", "what role should I target", "generate resume", "create resume variant", any resume generation request
This skill runs once per candidate profile, then the output is reused across all JD-specific tailoring.
A recruiter must identify your role identity within 6 seconds. A resume that says "I know 30 technologies" communicates nothing. A resume that says "I'm an AI/ML engineer who builds production ML systems with Python and FastAPI" communicates everything.
Positioning happens BEFORE keyword optimization. You cannot optimize what you haven't positioned.
Analyze the candidate's full profile (INPUT 2) across these dimensions:
| Signal | Weight | What to Extract |
|---|---|---|
| Job titles | High | Direct role identity (e.g., "AI Intern" → AI/ML signal) |
| Technologies used at work | High | Production-level tech stack |
| Project domains | Medium | What problems they solve (ML, web apps, CLI tools, infra) |
| Certifications | Medium | Industry validation direction (Azure AI, AWS, etc.) |
| Education focus | Low | Coursework alignment |
Count how many projects use each technology category:
Based on the profile analysis, classify into ONE primary and ONE secondary role family.
| Role Family | Key Signals |
|---|---|
| SDE / Software Engineer | Strong DSA, multiple languages, backend/API work, system design, production software |
| AI/ML Engineer | ML models, LLMs, RAG, AI agents, data pipelines, Python-heavy, research papers |
| Full Stack Developer | React/frontend + Node/backend, MERN/MEAN, responsive UI, authentication, RBAC |
| DevOps / Cloud Engineer | Docker, Kubernetes, CI/CD, cloud certifications, infrastructure, monitoring |
| Data Engineer | ETL pipelines, Spark, Kafka, data warehouses, SQL-heavy, streaming |
## Role Family Classification
**Primary:** AI/ML Engineer
**Evidence:** 3/6 projects are ML/AI, AI internship, Azure AI + Oracle AI certifications, LangGraph/CrewAI/RAG experience
**Secondary:** Software Engineer (Backend)
**Evidence:** FastAPI, REST APIs, Docker, Node.js/Express, database design
Select 8-12 core technologies that define this candidate for the primary role family. These are the technologies that MUST appear prominently in the resume.
For SDE:
Core: Python, C++, JavaScript, TypeScript, SQL, FastAPI, Node.js, Express, React, Docker, Git
Remove/Minimize: CrewAI, LangGraph, RAG, Neo4j, Azure OpenAI, FAISS, LangChain
For AI/ML Engineer:
Core: Python, ML, Scikit-learn, LLMs, RAG, LangGraph, FastAPI, FAISS, Elasticsearch, Docker, Git
Remove/Minimize: Next.js, Tailwind CSS, Bootstrap, Prisma ORM, GraphQL
For Full Stack:
Core: React, Next.js, Node.js, Express, TypeScript, MongoDB, MySQL, REST APIs, Docker, Git, Tailwind CSS
Remove/Minimize: CrewAI, LangGraph, FAISS, Elasticsearch, Neo4j, Isolation Forest
Rank ALL candidate projects by relevance to the primary role family. Output a priority list with selection recommendations.
| Factor | Weight |
|---|---|
| Technology overlap with core identity | 40% |
| Problem domain relevance | 25% |
| Architecture complexity | 20% |
| Deployment/demo evidence | 15% |
## Project Priority for [Role Family]
### Include on Resume (Top 2-3)
1. **[Project Name]** — [Why it fits: covers X core technologies, demonstrates Y]
2. **[Project Name]** — [Why it fits]
3. **[Project Name]** — [Why it fits, if space permits]
### Keep in Portfolio Only
4. **[Project Name]** — [Good project but doesn't fit this role variant]
5. **[Project Name]** — [Domain mismatch for this role]
### Recommendation
Lead with [Project 1] — it covers [N] critical technologies and demonstrates [problem-solving type].
Determine the Technical Skills section layout for the resume.
SDE:
Languages: Python, C++, JavaScript, TypeScript, SQL
Backend: FastAPI, Node.js, Express.js, REST APIs
Frontend: React.js, HTML5, CSS3
Tools: Docker, Git, GitHub, CI/CD
Databases: MongoDB, MySQL, PostgreSQL
AI/ML:
Languages: Python, SQL, JavaScript
AI/ML: Scikit-learn, LLMs, RAG, LangGraph, CrewAI, FAISS
Backend: FastAPI, REST APIs, Elasticsearch
Cloud: Azure AI, AWS, Docker, CI/CD
Databases: MongoDB, PostgreSQL, Neo4j
Select 2-3 certifications most relevant to the primary role family.
This brief is consumed by ALL downstream stages (JD Analyzer, Bullet Generator, Humanizer, Critic).
## Candidate Position Brief
**Candidate:** [Name]
**Primary Role:** [Role Family]
**Secondary Role:** [Role Family]
**Generated:** [Date]
### Core Technical Identity (8-12 technologies)
[Ordered list]
### Project Priority
1. [Project] — Include
2. [Project] — Include
3. [Project] — Include if space
4. [Project] — Portfolio only
...
### Skill Section Layout
[Category: items] format
### Certifications to Include
1. [Cert]
2. [Cert]
### Technologies to Remove/Minimize
[List with reasons]
### Candidate Positioning Statement
(1-2 sentence identity used internally, NOT placed on resume)
"[Name] is an AI/ML-focused backend engineer with internship experience building
ML systems and multiple deployed AI projects. Strongest in Python, FastAPI,
and ML pipeline development."
まだレビューはありません。使ってみた感想をお寄せください。
ログインなしで書き込めます。使ってみた感想、質問、動かなかった環境などを気軽にどうぞ。
まだコメントはありません。最初のコメントを書いてみませんか。
Format CVs for academic positions with publications, grants, and teaching
日本語の概要は準備中です。原文の説明を表示しています。
Decides whether to apply to a specific role, with what level of effort, and with which resume variant. Prevents wasted applications on roles with fundamentally poor fit and prioritizes high-probability opportunities.
日本語の概要は準備中です。原文の説明を表示しています。
Decide how to prioritize job applications using hard eligibility, evidence coverage, role alignment, and real application outcomes rather than arbitrary fit scores.
日本語の概要は準備中です。原文の説明を表示しています。
Define a clear primary role identity and supporting evidence so a resume reads coherently for the target job.
日本語の概要は準備中です。原文の説明を表示しています。
Translate skills from one industry to another, identify transferable skills
日本語の概要は準備中です。原文の説明を表示しています。
Create personalized, compelling cover letters from resume and job description
日本語の概要は準備中です。原文の説明を表示しています。