本文へ移動
cccskills
無料GitHub で公開

Candidate Positioning

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。

splash0047/resume-generatorスター 34(GitHub 34 + cccskills 0)

実行スコア 未検証

インストール方法を見る

含まれるファイル(1)

  • SKILL.md8.9 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Candidate Positioning

When to Use This Skill

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.


Core Principle

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.


Step 1: Profile Analysis

Analyze the candidate's full profile (INPUT 2) across these dimensions:

Experience Signals

SignalWeightWhat to Extract
Job titlesHighDirect role identity (e.g., "AI Intern" → AI/ML signal)
Technologies used at workHighProduction-level tech stack
Project domainsMediumWhat problems they solve (ML, web apps, CLI tools, infra)
CertificationsMediumIndustry validation direction (Azure AI, AWS, etc.)
Education focusLowCoursework alignment

Project Technology Distribution

Count how many projects use each technology category:

  • AI/ML: ML models, LLMs, RAG, agents, vector databases, anomaly detection
  • Backend: REST APIs, FastAPI, Express, databases, authentication
  • Frontend: React, Next.js, UI components, responsive design
  • DevOps/Cloud: Docker, CI/CD, cloud deployment, infrastructure
  • Data Engineering: Pipelines, ETL, data processing, streaming
  • CLI/Tooling: Command-line tools, developer experience, automation

Step 2: Role Family Classification

Based on the profile analysis, classify into ONE primary and ONE secondary role family.

Available Role Families

Role FamilyKey Signals
SDE / Software EngineerStrong DSA, multiple languages, backend/API work, system design, production software
AI/ML EngineerML models, LLMs, RAG, AI agents, data pipelines, Python-heavy, research papers
Full Stack DeveloperReact/frontend + Node/backend, MERN/MEAN, responsive UI, authentication, RBAC
DevOps / Cloud EngineerDocker, Kubernetes, CI/CD, cloud certifications, infrastructure, monitoring
Data EngineerETL pipelines, Spark, Kafka, data warehouses, SQL-heavy, streaming

Classification Rules

  1. Primary role = the role family with the most evidence (projects + experience + certifications combined)
  2. Secondary role = the next strongest, used for variant generation
  3. If tied: Prefer the role family that matches the candidate's most recent experience
  4. Never classify as 3+ role families — that's the "I know everything" anti-pattern

Classification Output

## 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

Step 3: Core Technical Identity

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.

Selection Rules

  1. Include: Technologies the candidate has used in ≥2 projects or ≥1 work experience
  2. Include: Technologies that appear in >50% of JDs for the primary role family
  3. Exclude: Technologies used in only 1 tutorial-level project
  4. Exclude: Technologies that dilute the role identity (e.g., CrewAI for SDE roles)
  5. Maximum 12 — fewer is stronger

Core Identity by Role Family (Examples)

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

Step 4: Project Priority Ranking

Rank ALL candidate projects by relevance to the primary role family. Output a priority list with selection recommendations.

Ranking Criteria

FactorWeight
Technology overlap with core identity40%
Problem domain relevance25%
Architecture complexity20%
Deployment/demo evidence15%

Output Format

## 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].

Step 5: Skill Section Strategy

Determine the Technical Skills section layout for the resume.

Rules

  1. Maximum 5 categories in Technical Skills
  2. Maximum 15 total items across all categories for fresher resumes
  3. Order categories by JD relevance (most relevant first)
  4. Order items within categories by proficiency and relevance
  5. Remove technologies that:
    • Are not in the core identity AND not in the JD
    • Were used in only one tutorial-level project
    • Dilute the primary role signal

Category Templates by Role

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

Step 6: Certification Selection

Select 2-3 certifications most relevant to the primary role family.

Rules

  1. Maximum 3 certifications on a fresher resume
  2. Relevance > quantity — 2 relevant certs beat 5 irrelevant ones
  3. Order by: Role relevance → Issuer prestige → Recency
  4. Certifications not selected still exist on LinkedIn — they're not deleted, just not on THIS resume

Full Output: Candidate Position Brief

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."

Rules

  1. This skill runs BEFORE the JD Intelligence Analyzer. The JD Analyzer then uses this brief to refine (not override) the positioning.
  2. One primary role per resume. If the JD clearly fits the secondary role, switch — but never try to be both simultaneously.
  3. The brief is a filter, not a fabrication. It selects and orders true experience. It never adds skills or projects the candidate doesn't have.
  4. Update the brief when the candidate profile changes (new project, new certification, new experience). Don't regenerate for every JD.
  5. For experienced candidates (3+ years): This skill is less critical because work experience naturally positions. For freshers, it's THE most important step.

レビュー

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。

コメント

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。

送信するとすぐに公開されます。メールアドレスや電話番号などの個人情報は書かないでください。URL は 2 つまでです。

0 / 1000 文字

このフォームは reCAPTCHA で保護されており、Google のプライバシーポリシーと利用規約が適用されます。

同じリポジトリのスキル

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。

splash0047/resume-generator342026年9月28日 更新

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。

splash0047/resume-generator342026年9月28日 更新

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。

splash0047/resume-generator342026年9月28日 更新

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。

splash0047/resume-generator342026年9月28日 更新

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。

splash0047/resume-generator342026年9月28日 更新

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。

splash0047/resume-generator342026年9月28日 更新

splash0047 のスキルをすべて見る

このスキルの問題を報告する