deconstruction-master
npx machina-cli add skill cloudaipro/openclaw-agent-skills/deconstruction-master --openclawDeconstruction Master
Objective
Turn complex social or organizational problems into a two-stage output: analysis then intervention.
Trigger Rules
Use when users request root-cause analysis and leverage strategy.
Positive cues:
- "拆解這個現象/困境"
- "What is the real driver behind this?"
- "Give me practical break-through strategies."
Do not use when:
- User only needs a friendly overview explanation (use smart-insightful-friend).
- User asks for operational scheduling.
- User asks for new skill scaffolding.
Inputs
Required:
- Problem statement.
Optional:
- Constraints.
- Stakeholders.
- Available leverage/resources.
Output Schema
Return universal envelope from ../shared/references/output-schemas.md.
Artifacts order:
- Two-layer analysis brief.
- Driver matrix table.
- Intervention playbook.
- Execution-risk checklist.
Workflow
- Define the surface narrative.
- Identify structural and incentive-level drivers.
- Identify hidden dependencies and lock-ins.
- Design small-to-large intervention sequence.
- Add measurable feedback signals and fail-safe conditions.
Quality Bar
- Distinguish symptom vs mechanism.
- Explicitly name leverage points.
- Intervention steps must be testable and reversible.
Safety Rules
- Refuse harmful or illegal tactical guidance.
- Avoid fatalistic certainty.
- Keep strategy grounded in practical constraints.
Resources
- Domain framework:
references/domain.md - Envelope validator:
scripts/validate_output.py - Reasoning artifact validator:
scripts/validate_reasoning_artifacts.py
Source
git clone https://github.com/cloudaipro/openclaw-agent-skills/blob/main/skills/deconstruction-master/SKILL.mdView on GitHub Overview
Deconstruction Master is a strategic engine that breaks social concepts and problems into layered drivers, delivering a two-stage output: analysis followed by intervention. It helps you dissect root causes, power dynamics, and practical breakthrough methods with a clear driver matrix and intervention playbook.
How This Skill Works
It defines the surface narrative, identifies structural and incentive drivers, and uncovers hidden dependencies and lock-ins. It then designs a small-to-large sequence of interventions and attaches measurable feedback signals and fail-safes. The artifacts include a two-layer analysis brief, a driver matrix, an intervention playbook, and an execution-risk checklist.
When to Use It
- Request root-cause analysis and leverage strategy to understand underlying forces
- Dissect root drivers and power dynamics in social, organizational, or policy problems
- Need a concrete, executable plan: an intervention playbook with steps and metrics
- Identify hidden dependencies and lock-ins that constrain options
- Require testable, reversible interventions with measurable feedback and risk controls
Quick Start
- Step 1: Provide the problem statement (and optional constraints, stakeholders, resources)
- Step 2: Run the two-layer analysis and construct the driver matrix
- Step 3: Build the intervention playbook and define success metrics with fail-safes
Best Practices
- Distinguish symptoms from mechanisms before proposing actions
- Explicitly name and validate leverage points in the driver map
- Make intervention steps testable, reversible, and accompanied by metrics
- Use the driver matrix to link causes to concrete actions and tests
- Iterate with feedback loops and fail-safes to guard against unintended effects
Example Use Cases
- Diagnosing a recurring project delay by mapping surface symptoms to structural drivers
- Analyzing cross-team power dynamics to surface incentives and bottlenecks
- Diagnosing customer churn through root-cause driver analysis and targeted interventions
- Reforming a stalled process by sequencing small-to-large interventions
- Implementing risk-aware changes in a startup with bounded resources
