Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Recovers broken agent state via crash recovery, context overflow, and merge conflict protocols. Use when an agent session fails or a worktree is corrupted.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Provides recovery protocols for agents that encounter broken state mid-session. Damage control covers four failure classes: agent crashes with partial work on disk, context window overflow that causes state loss, merge conflicts blocking forward progress, and general session state corruption requiring reconciliation.
The skill does not prevent failures. It defines what to do after one has already happened, so recovery is consistent, auditable, and does not silently discard work.
git merge or git rebase produced conflicts the agent cannot
resolve automaticallySkill(leyline:risk-classification) instead)Skill(attune:war-room) instead)Skill(leyline:error-patterns) instead)Use this decision tree to route to the correct module:
flowchart TD
A[Failure detected] --> B{Agent process crashed\nor exited unexpectedly?}
B -->|Yes| C[modules/crash-recovery.md]
B -->|No| D{Context limit hit or\nprior decisions unavailable?}
D -->|Yes| E[modules/context-overflow.md]
D -->|No| F{git merge / rebase /\ncherry-pick conflicts?}
F -->|Yes| G[modules/merge-conflict-resolution.md]
F -->|No| H{State internally inconsistent?\ntask list vs disk vs git index}
H -->|Yes| I[modules/state-reconciliation.md]
H -->|No| J[No damage-control needed]
When multiple failure types overlap, start with
state-reconciliation.md to establish a known baseline, then
address the specific failure class.
Before executing Level 1+ tasks, complete the risk assessment
checklist from modules/risk-assessment-checklist.md. Answer
these five questions:
Required for Level 1 (Watch) and above. See
modules/risk-assessment-checklist.md for the full template and
examples.
# In your skill's frontmatter
dependencies: [leyline:damage-control]
Invoke a specific module when a failure class is identified:
# Crash detected
Skill(leyline:damage-control) → modules/crash-recovery.md
# Context limit reached
Skill(leyline:damage-control) → modules/context-overflow.md
For orchestrators managing multiple agents, invoke state-reconciliation at session boundaries regardless of whether a failure occurred. This establishes a verified checkpoint before the next work phase begins.
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Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.