constraint-identification
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/constraint-identificationIdentify implementation blockers using structured constraint analysis techniques
- Pinpoints bottlenecks, contradictions, and failure risks in candidate solutions
- Uses Theory of Constraints, TRIZ, and Pre-mortem analysis frameworks
- Classifies constraints into hard, soft, and assumptions with removal paths
- Produces structured constraint inventory for risk-informed decision making
SKILL.md
.github/skills/constraint-identificationView on GitHub ↗
---
name: constraint-identification
description: Find blockers and showstoppers using TOC, TRIZ contradiction analysis, and Pre-mortem techniques.
used-by: feasibility-assessment
---
# Constraint Identification
**Purpose:** Systematically discover what could prevent a candidate from being implemented. Uses Theory of Constraints to find bottlenecks, TRIZ to surface contradictions, and Pre-mortem to anticipate failures before they occur.
**When to use:**
- A candidate looks promising but you need to stress-test its viability
- Stakeholders want to know what could go wrong before committing
- You need a structured inventory of blockers with severity and removability assessments
## Budget
| Metric | Target |
|--------|--------|
| Constraints identified | >= 3 per candidate |
| Hard constraints classified | >= 1 |
| Removal paths designed | >= 1 per removable constraint |
## State Ledger
| Key | Type | Description |
|-----|------|-------------|
| candidate | object | The candidate under assessment |
| constraints[] | array | All identified constraints |
| hard_constraints[] | array | Non-negotiable blockers |
| soft_constraints[] | array | Constraints that can be worked around |
| assumptions[] | array | Unvalidated beliefs that may become constraints |
| removal_paths{} | map | Constraint -> removal path mapping |
## Available Tactics
| Tactic | When |
|--------|------|
| constraint-drilling | Default — full constraint discovery, classification, and removal path design |
## Available SOPs
| SOP | Purpose |
|-----|---------|
| constraint-identification-sop | Discover constraints |
| constraint-classification | Sort into hard/soft/assumptions |
| removability-assessment | Score how removable each constraint is |
| removal-path | Design steps to remove a constraint |
## Execution Guidance
1. Deploy `constraint-identification-sop` to discover all constraints using TOC, TRIZ, and Pre-mortem
2. Feed discovered constraints to `constraint-classification` to sort them
3. For each non-trivial constraint, run `removability-assessment`
4. For constraints with removability score > 0.3, design `removal-path`
5. Aggregate findings into state ledger
## Output Format
```yaml
constraint_analysis:
candidate: <name>
total_constraints: N
hard_constraints:
- {constraint, severity, rationale}
soft_constraints:
- {constraint, severity, workaround_sketch}
assumptions:
- {assumption, risk_if_false, validation_method}
removal_paths:
- {constraint, removability: 0.X, steps: [...], timeline, resources}
showstopper_verdict: <yes/no>
showstopper_reason: <if yes>
```
More from yogsoth-ai/de-anthropocentric-research-engine
- abductive-hypothesis-generationStrategy: 面对异常的最佳解释推理
- ablation-brainstormRemove components one by one, observe system changes to reveal hidden dependencies and generate ideas from structural gaps.
- ablation-component-mappingMap system architecture to ablatable units for ablation studies
- ablation-designDesign ablation studies to isolate component contributions in ML systems
- ablation-executionRemove components one by one from a system, record the response/impact of each removal.
- abp-vulnerability-classificationClassify assumptions on 2 axes — load-bearing (how much conclusion depends on it) × vulnerable (how likely to be false). Focuses attention on High-Load × High-Vulnerable quadrant.
- abstraction-extractionExtract abstract principles from concrete domain cases. Strips domain-specific details to reveal transferable mechanisms.
- abstraction-ladderPerform bisociation at multiple abstraction levels
- abstraction-ladderingMove between concrete and abstract framings — 3 levels up (Why?) and 3 levels down (How?) to find the most productive research level.
- abstraction-to-designAbstract biological principle to design principle. Bridge from biology to engineering.