refactor(topics): 멀티 에이전트용 지식 재편 — _Common(공통 기본기) + Domain_* 구조
에이전트 8종(대화형/프로그래머 C·S/디자이너/설계자/기획자/QA/PD/PM)에게 [공통 기본 능력 + 롤별 Specialty] 2층으로 지식을 주입하기 위한 재분류. 문서 내용·포맷은 무수정, 폴더 이동만 (6,372개 문서 수 보존 확인). - Topic_Programming → Domain_Programming (내부 구조 보존) - Topic_Graphic → Domain_Design - Topic_Business → Domain_Product - Topic_General → Domain_General - _Common 신설: Math(구 Topic_Math_Specialty), Reasoning(구 General/From_Thinking & Reasoning), Reasoning_Creativity(구 General/From_창의성), Communication(Poetic_Blog_Writing + From_writing) - 타 도메인의 From_* 폴더는 유지 (출처 표기일 뿐, 이미 도메인에 맞게 분류된 문서) - 빈 폴더 정리 (memory/procedures) - 에이전트→폴더 매핑은 workspace의 .astra/agent-knowledge-map.json (9개 에이전트) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Antigravity Agent
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---
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id: wiki-2026-0508-reflection
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title: Reflection
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [Self-Reflection, Reflexion, Programming Reflection]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.9
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verification_status: applied
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tags: [reflection, metaprogramming, llm, reflexion, self-critique]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: python
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framework: anthropic-sdk
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---
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# Reflection
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## 매 한 줄
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> **"매 program inspects itself, agent critiques itself"**. Reflection 은 dual concept — programming 에서 runtime 의 type/method introspection, AI 에서 LLM 의 self-critique loop. 2023 Reflexion paper (Shinn) 가 후자를 popularize, 2026 의 agent loop 의 backbone.
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## 매 핵심
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### 매 Programming Reflection
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- **Java**: `Class.forName`, `Method.invoke` — runtime type lookup.
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- **Python**: `getattr`, `inspect`, `type()` — first-class.
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- **Go**: `reflect.ValueOf`, `reflect.TypeOf` — verbose but explicit.
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- **Rust**: 매 limited — `std::any::Any`, no runtime method dispatch.
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- **Cost**: 매 10-100x slower than direct call. JIT 의 mitigates partially.
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### 매 LLM Reflection
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- **Reflexion (2023)**: agent generates → critiques → retries with verbal feedback in context.
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- **Self-critique**: 매 model evaluates own output against rubric/spec.
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- **Constitutional AI**: Anthropic 의 자기-revision against principles.
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- **CRITIC (2024)**: tool-augmented self-correction.
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- **Test-time compute (o1, Claude thinking)**: 매 internal reflection 의 productized.
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### 매 응용
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1. Agent error recovery — failed tool call 의 self-diagnose.
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2. Code generation — write → test → fix loop.
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3. Math/logic — chain-of-thought + verifier.
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4. Plugin systems — runtime method discovery.
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5. ORM — entity-to-table reflection mapping.
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## 💻 패턴
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### Python introspection
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```python
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import inspect
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class Service:
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def fetch(self, url: str) -> dict: ...
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def post(self, url: str, body: dict) -> None: ...
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svc = Service()
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for name, method in inspect.getmembers(svc, predicate=inspect.ismethod):
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sig = inspect.signature(method)
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print(f"{name}{sig}")
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```
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### Go reflect (struct tags)
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```go
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type User struct {
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Name string `json:"name" validate:"required"`
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Email string `json:"email" validate:"email"`
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}
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func validate(v any) error {
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t := reflect.TypeOf(v)
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val := reflect.ValueOf(v)
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for i := 0; i < t.NumField(); i++ {
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tag := t.Field(i).Tag.Get("validate")
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if tag == "required" && val.Field(i).IsZero() {
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return fmt.Errorf("%s required", t.Field(i).Name)
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}
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}
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return nil
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}
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```
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### Reflexion loop (Claude Opus 4.7)
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```python
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from anthropic import Anthropic
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client = Anthropic()
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MODEL = "claude-opus-4-7"
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def reflexion(task: str, max_iter: int = 3) -> str:
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history = []
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attempt = generate(task, history)
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for i in range(max_iter):
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critique = client.messages.create(
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model=MODEL,
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max_tokens=1024,
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messages=[{
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"role": "user",
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"content": f"Task: {task}\nAttempt: {attempt}\n"
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f"Critique: list errors, missing edge cases. "
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f"If perfect, reply DONE."
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}]
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).content[0].text
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if "DONE" in critique:
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return attempt
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history.append({"attempt": attempt, "critique": critique})
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attempt = generate(task, history)
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return attempt
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def generate(task: str, history: list) -> str:
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ctx = "\n".join(f"Prev attempt: {h['attempt']}\nCritique: {h['critique']}"
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for h in history)
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resp = client.messages.create(
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model=MODEL,
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max_tokens=2048,
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messages=[{"role": "user", "content": f"{ctx}\n\nTask: {task}"}]
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)
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return resp.content[0].text
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```
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### Self-critique with extended thinking
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```python
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# Claude Opus 4.7 의 native thinking — implicit reflection
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resp = client.messages.create(
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model="claude-opus-4-7",
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max_tokens=8192,
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thinking={"type": "enabled", "budget_tokens": 4096},
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messages=[{"role": "user", "content": "Solve: ..."}]
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)
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# resp.content[0].type == "thinking" — reflection trace
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# resp.content[1].type == "text" — final answer
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```
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### Plugin discovery (Java)
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```java
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ServiceLoader<Plugin> loader = ServiceLoader.load(Plugin.class);
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for (Plugin p : loader) {
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Method init = p.getClass().getMethod("init", Config.class);
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init.invoke(p, cfg);
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}
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```
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## 매 결정 기준
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| 상황 | Approach |
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|---|---|
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| Hot loop performance | 매 reflection X — codegen / direct call |
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| Plugin / DI framework | Reflection OK (one-time init) |
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| LLM agent error recovery | Reflexion loop (max 3 iter) |
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| Math/code with verifier | Self-critique + tool execution |
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| Chat UX | Extended thinking (native) |
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**기본값**: 매 native thinking (Claude Opus 4.7) 의 first try, explicit Reflexion 의 verifiable domain (code/math).
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## 🔗 Graph
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- 부모: [[Metaprogramming]]
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- 변형: [[Reflexion]] · [[AI_Safety_and_Alignment|Constitutional-AI]] · [[Self-Consistency]]
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- 응용: [[Code-Generation]] · [[Tool-Use]]
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- Adjacent: [[Chain-of-Thought]]
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## 🤖 LLM 활용
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**언제**: 매 verifiable output (code passes tests, math 의 numerical), expensive failures (production agent), multi-step planning.
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**언제 X**: simple Q&A (reflection 의 cost > benefit), creative generation (critique 의 collapse to mean), latency-critical (<500ms).
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## ❌ 안티패턴
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- **Infinite reflection**: 매 max_iter cap 없음 → cost runaway.
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- **Critic = generator**: same model 의 critique 의 weak — 매 stronger verifier 의 use.
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- **Reflection in hot path**: Java/Go 의 production code 의 reflect.Value 의 hide.
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- **Verbal-only critique**: 매 numeric/test signal 없음 → noise.
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- **Self-praise loop**: critique prompt 의 "find ANY issue" 의 biased.
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## 🧪 검증 / 중복
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- Verified (Reflexion paper 2023, Anthropic Constitutional AI, Java/Go reflect docs).
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- 신뢰도 A.
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — programming + LLM reflection unified |
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