dissolve-form
정보
`dissolve-form` 스킬은 핵심 기능을 보존하면서 경직되고 경화된 시스템 구조를 통제적으로 해체합니다. 이 스킬은 기술 부채가 모든 진전을 막거나 점진적 변경이 불가능한 상황, 일반적으로 `assess-form` 평가 이후에 사용됩니다. 해당 프로세스에는 경직성 매핑, 해체 순서 설정, 안전한 분해가 포함되어 시스템을 연화시켜 후속 아키텍처 재구성을 가능하게 합니다.
빠른 설치
Claude Code
추천npx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/dissolve-formClaude Code에서 이 명령을 복사하여 붙여넣어 스킬을 설치하세요
문서
Dissolve Form
Controlled dismantle of rigid systems → dissolve calcified arch + tech debt + org rigidity, preserve imaginal discs → seed new form.
Use When
assess-form→ PREPARE or CRITICAL (too rigid to transform direct)- So calcified incremental change impossible
- Tech debt blocks all fwd progress
- Org structure too rigid for new reqs
- Before
adapt-architecture→ soften before reshape - Legacy decommission → extract value before shutdown
In
- Required: Form assessment → high rigidity (
assess-form) - Required: ID essential capabilities → preserve (imaginal discs)
- Optional: Target form (post-dissolve; may be unknown)
- Optional: Timeline + constraints
- Optional: Stakeholder concerns on specific components
- Optional: Prior dissolve attempts + outcomes
Do
Step 1: ID Imaginal Discs
Bio metamorphosis → imaginal discs = cell clusters in caterpillar → survive dissolve → become butterfly organs. ID what must survive.
- Catalog every capability:
- User features
- Data processing
- External integrations
- Institutional knowledge in code/process
- Business rules (often implicit, undoc)
- Classify:
- Imaginal disc (must survive): core biz logic, critical integrations, irreplaceable data
- Replaceable tissue (rebuild): UI, infra, standard algos
- Dead tissue (discard): workarounds for fixed bugs, shims for dead systems, unused features
- Extract imaginal discs → portable:
- Doc biz rules explicit (may only exist as comments or tribal)
- Extract algos → standalone tested modules
- Export data → format-independent
- Record integration contracts + actual (not doc) behavior
→ Clear capability inventory: preserve/rebuild/discard. Essentials extracted portable before dissolve starts.
If err: imaginal disc ID uncertain (stakeholder disagree) → err on preserve side. Extract more than need → discard after dissolve easy, recover lost knowledge often impossible.
Step 2: Map Dissolve Sequence
Order → outer layers first, core last.
- Order by dep depth:
- L1 (outermost): no dependents → nothing breaks on remove
- L2: dependents only in L1 (already dissolved)
- L3: deeper deps → careful interface mgmt
- LN (core): load-bearing → dissolved last
- Per layer:
- What dissolved (removed, decommission, archive)
- What replaces (new comp, nothing, stub)
- Interfaces to maintain for remaining layers
- How verify post-dissolve
- Dissolve checkpoints:
- Post-layer → tested + verified operational
- Each checkpoint = stable state → pause poss
- If layer dissolve breaks → restore prior checkpoint
Dissolution Sequence (outside in):
┌─────────────────────────────────────────────────────────────────┐
│ Layer 1: Dead features, unused integrations, orphaned code │
│ → Remove. Nothing depends on these. │
│ │
│ Layer 2: Replaceable UI, standard infrastructure │
│ → Replace with modern equivalents or stubs │
│ │
│ Layer 3: Business logic wrappers, data access layers │
│ → Extract imaginal discs, then dissolve │
│ │
│ Layer 4 (core): Load-bearing structures, data stores │
│ → Dissolve last, with full replacement ready │
└─────────────────────────────────────────────────────────────────┘
→ Layer-ordered sequence, each step safe (checkpoint) + reversible (prior checkpoint restorable). Most critical dissolved last when team has most exp + confidence.
If err: dep mapping reveals circular (A→B→A) → break cycle first. Add interface A↔B, break cycle, then proceed.
Step 3: Interface Archaeology
Before dissolve → excavate + doc actual interfaces, not documented, actual in use.
- Instrument interfaces:
- Log every call/msg/exchange at each interface
- Run ≥1 full biz cycle (daily/weekly/monthly)
- Capture actual payload shapes, not just doc schemas
- Compare actual vs documented:
- Doc interfaces never called? (L1 candidates)
- Undoc interfaces actively used? (hidden deps → preserve or explicit replace)
- Edge cases in traffic doc doesn't mention
- Build contract from actual behavior:
- Contract → spec for replacement
- Real input/output examples
- Doc actual error handling (not should-be)
→ Empirical contract: actual communication + undoc behaviors + hidden deps.
If err: instrumentation too invasive (perf or code changes) → sample traffic. Biz cycle too long → available data + stakeholder interviews on "what calls what when".
Step 4: Execute Dissolve
Systematic remove + maintain imaginal disc viability.
- Start L1 (outermost, no dependents):
- Remove dead features + unused code
- Archive (don't delete) for reference
- Verify: all tests pass, no runtime errs
- Per layer:
- Per component dissolved: a. Verify imaginal discs extracted (Step 1) b. Install replacement or stub (if dependents remain) c. Remove component d. Run valid. suite e. Monitor for side effects
- Per checkpoint: doc state + verify operational
- Handle resistance:
- Some resist (hidden deps surface)
- When remove breaks: a. Restore checkpoint b. Investigate hidden dep c. Add to interface archaeology (Step 3) d. Explicit stub for dep e. Re-attempt
- Track progress:
- Components remaining vs dissolved
- Imaginal discs extracted + verified portable
- Unexpected deps found + handled
→ Systematic verified dissolve of non-essential. Post-layer: smaller, simpler, operational. Imaginal discs preserved portable.
If err: cascading failure → layer order wrong, hidden deps deeper than expected. Stop, restore, remap deps, re-sequence. Imaginal disc more complex than expected → more extract time.
Step 5: Prep Foundation for Reconstruction
Post-dissolve → minimal viable core + extracted imaginal discs ready.
- Assess post-state:
- What remains? (minimal core + extracted capabilities)
- Maintainable? (team understands + modifies)
- All imaginal discs accessible + verified? (portable + tested + doc'd)
- Reconstruction manifest:
- Per disc: contract + data + test suite
- Target arch (or TBD)
- Gaps: partial extracts or quality concerns
- Handoff:
- Target known →
adapt-architecturew/ minimal core - Target unknown → operate on minimal core while designing
- Either way: system flexible → reshape-able
- Target known →
→ Minimal maintainable system + doc'd extracted capabilities. Foundation clean, ready for reconstruction in any form.
If err: post-state less maintainable than expected → some essential was dissolved. Check imaginal disc inventory → if critical capability missing, may still be in archive. Minimal core too minimal → "replaceable" was actually essential → restore from checkpoint.
Check
- Imaginal discs IDed + extracted + verified portable
- Sequence: outermost (no dependents) → core
- Interface archaeology → actual (not just doc) behavior
- Each layer verified checkpoint
- No essential lost
- Post-state minimal + maintainable + operational
- Reconstruction manifest: capabilities + gaps
Traps
- Dissolve w/o extract: Remove rigid component before extract → destroys irreplaceable knowledge. Extract imaginal discs first.
- Trust docs over observation: Docs often diverge from actual. Interface archaeology reveals truth, docs show intent.
- Core first: Load-bearing before dependents → cascading failure. Outside-in.
- Total dissolve: Everything gone "clean slate" → lose institutional knowledge, edge-case handling, operational continuity. Preserve imaginal discs.
- Dissolve as punishment: "Because it's bad" w/o reconstruction plan → vacuum. Dissolve is prep for rebuild, not end itself.
→
assess-form— prereq assessment → IDs rigidity, triggers dissolveadapt-architecture— reconstruction after dissolverepair-damage— targeted repair vs full dissolvebuild-consensus— consensus before dissolve → prevents team fragmentationdecommission-validated-system— formal decommission for regulatedconduct-post-mortem— shares investigative rigor w/ dissolve
GitHub 저장소
연관 스킬
llamaguard
기타LlamaGuard는 폭력 및 혐오 발언 등 6가지 안전 범주에서 LLM 입력과 출력을 조정하기 위한 Meta의 70-80억 파라미터 모델입니다. 94-95% 정확도를 제공하며 vLLM, Hugging Face 또는 Amazon SageMaker를 사용해 배포할 수 있습니다. 이 기술을 사용하여 AI 애플리케이션에 콘텐츠 필터링 및 안전 가드레일을 손쉽게 통합하세요.
cost-optimization
기타이 Claude Skill은 리소스 적정화, 태깅 전략, 지출 분석을 통해 개발자들이 클라우드 비용을 최적화할 수 있도록 지원합니다. AWS, Azure, GCP에서 클라우드 비용을 절감하고 비용 거버넌스를 구현하기 위한 프레임워크를 제공합니다. 인프라 비용을 분석하거나, 리소스를 적정화하거나, 예산 제약을 충족해야 할 때 사용하세요.
quantizing-models-bitsandbytes
기타이 스킬은 bitsandbytes를 사용하여 LLM을 8비트 또는 4비트 정밀도로 양자화하며, 최소한의 정확도 손실로 50-75%의 메모리 감소를 달성합니다. 제한된 GPU 메모리에서 더 큰 모델을 실행하거나 추론을 가속화하는 데 이상적이며, INT8, NF4, FP4와 같은 형식을 지원합니다. 이 스킬은 HuggingFace Transformers와 통합되어 QLoRA 학습 및 8비트 옵티마이저를 가능하게 합니다.
dispatching-parallel-agents
기타이 Claude Skill은 3개 이상의 독립적인 문제를 동시에 조사하고 해결하기 위해 다중 에이전트를 배치합니다. 공유 상태나 의존성 없이 해결 가능한 무관련 장애 시나리오에 맞게 설계되었습니다. 핵심 기능은 병렬 문제 해결로, 각 독립 문제 영역마다 하나의 에이전트를 할당하여 효율성을 극대화합니다.
