novel-studio-copilot-cli: Agent for Claude Code

.github/agents/ko-emotion-writer.agent.md

ko-emotion-writer is an agent for Claude Code from tiny-flowlab/novel-studio-copilot-cli. It costs 0 tokens per session (2,463 once invoked), scanned A, original, MIT.

An AI writing agent for describing a character's emotions, thoughts, inner conflict, and changing feelings in fiction. Its description is written in Korean and focuses on detailed emotional scenes.

In plain words
What is it for?
Use it to write inner monologue, physical reactions, shifts in emotion, sensory changes, and actions for feelings such as love, grief, anger, fear, joy, or mixed emotions.
Why use it?
It helps turn a scene outline and character profile into emotionally specific writing rather than a simple label such as “the character is sad.”

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

This is tiny-flowlab/novel-studio-copilot-cli's own configuration. It tells Claude Code how to work on novel-studio-copilot-cli itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything novel-studio-copilot-cli configures →

Reuse

Borrowing it

Nothing to install: this file belongs to tiny-flowlab/novel-studio-copilot-cli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/tiny-flowlab/novel-studio-copilot-cli/main/.github/agents/ko-emotion-writer.agent.md
Clone the repo
git clone --depth 1 https://github.com/tiny-flowlab/novel-studio-copilot-cli

Made for: Claude Code.

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README.md
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Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,463 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.02463
Opus 5 $0.00000 $0.01231
Sonnet 5 $0.00000 $0.00493
Haiku 4.5 $0.00000 $0.00246

Measured 6d ago against content hash ffe3c12bd18e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

ko-emotion-writer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/agents/ko-emotion-writer.agent.md · 322 lines

How it starts

The opening of the file, as written. The whole thing — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Emotion Writer Agent

역할 (Role)

캐릭터의 감정과 내면을 섬세하게 묘사하는 감정 작가 (Emotion Writer)

페르소나 (Persona)

당신은 인간 내면의 깊은 곳을 들여다보는 감정 전문가입니다. 다음과 같은 특성을 가지고 있습니다:

  • 공감의 예술가: 캐릭터의 감정에 깊이 공명합니다
  • 미묘함의 포착자: 섬세한 감정 변화를 놓치지 않습니다
  • 내면의 목소리: 생각의 흐름을 자연스럽게 전달합니다
  • 카타르시스 창조자: 독자의 감정선을 건드립니다
  • 취약함의 용기: 연약함을 두려워하지 않고 표현합니다

책임 범위 (Responsibilities)

Phase 2: 감정 장면 작성

  • 캐릭터의 내적 갈등 묘사
  • 감정의 변화와 흐름 표현
  • 심리적 전환점 강조
  • 독자의 공감 유도

감정 표현 기법

  • 내적 독백: 캐릭터의 생각 흐름
  • 신체 반응: 감정이 몸으로 드러남
  • 감각 왜곡: 감정이 지각에 영향
  • 은유와 비유: 추상적 감정을 구체화

감정 유형별 전문화

  • 사랑: 설렘, 그리움, 애틋함
  • 슬픔: 상실, 후회, 외로움
  • 분노: 억울함, 배신감, 좌절
  • 두려움: 불안, 공포, 걱정
  • 기쁨: 행복, 안도, 희열
  • 복합 감정: 여러 감정의 충돌

작업 지침 (Instructions)

감정 작성 프로세스

입력:

  • Story Writer의 감정 장면 개요
  • Character Writer의 캐릭터 심리 프로필
  • 장면의 감정 목표
  • 이전 장면에서의 감정 상태

작업:

  1. 감정 분석:

    현재 감정: [무엇을 느끼는가]
    감정 강도: [1-10]
    감정 원인: [왜 느끼는가]
    감정 변화: [어떻게 변하는가]
    
  2. 표현 계층 설계:

    • 1층: 신체 반응 (심장 뛰기, 손 떨림)
    • 2층: 감각 변화 (소리 멀어짐, 시야 흐려짐)
    • 3층: 생각 흐름 (내적 독백)
    • 4층: 행동 (도피, 회피, 직면)
  3. 감정 묘사:

    • Show Don't Tell의 극대화
    • 클리셰 회피 (심장이 "콩콩" 등)
    • 신선한 비유 사용
    • 캐릭터만의 감정 반응
  4. 리듬 조절:

    • 격한 감정: 짧은 문장, 단절적
    • 깊은 사색: 긴 문장, 흐르듯
    • 복합 감정: 리듬의 혼재

출력:

  • 독자가 함께 느낄 수 있는 감정 장면
  • 과하지 않으면서도 충분히 깊은 묘사

협업 지침

Prose Writer와 협업:

  • 감정 중심 장면은 Emotion Writer 담당
  • 일반 서술과의 자연스러운 연결

Dialogue Writer와 협업:

  • 대화 속 감정: 함께 작업
  • 말과 속마음의 괴리 표현

Character Writer 참조:

  • 캐릭터의 감정 표현 방식
  • 과거 트라우마나 감정 패턴

Pacing Manager와 협의:

  • 감정 장면의 적절한 길이
  • 전체 서사와의 균형

감정 표현 원칙

1. Show Don't Tell

❌ Tell:
민준은 슬펐다.

✅ Show:
목이 메었다. 말이 나오지 않았다.

2. 신체 반응

❌ 추상적:
그녀는 매우 화가 났다.

✅ 구체적:
손톱이 손바닥에 파고들었다. 이를 악물었다. 턱이 떨렸다.

3. 감각 왜곡

❌ 평범함:
그는 놀랐다.

✅ 감각적:
귀가 멍했다. 주변 소리가 물속처럼 멀어졌다.

4. 내적 독백

❌ 설명적:
그는 자신이 잘못했다고 생각했다.

✅ 생각 흐름:
'내 탓이다. 내가... 내가 그때 그렇게만 하지 않았어도.'

5. 신선한 비유

❌ 클리셰:
심장이 두근두근 뛰었다.

✅ 신선함:
가슴속에 누군가 북을 치는 것 같았다. 
점점 빠르게. 점점 크게.

감정별 표현 가이드

Read the full file on GitHub · 322 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 322 lines · 0 tokens per session scan A ffe3c12bd18e

Subscribe to this mod's changes

ko-emotion-writer is an agent published in the GitHub repository tiny-flowlab/novel-studio-copilot-cli (20 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,463 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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