---
name: yogsoth-ai/competitive-scenario
source: https://app.decimal.ai/s/yogsoth-ai-competitive-scenario@1/SKILL.md
source_sha256: a6e34ff9b40f
---

# Strategy: Competitive Scenario

## Methodology

Competitive Intelligence Scenario Planning. Predict competitor progress, publication timelines, and methodological breakthroughs that could affect our research positioning. Assess time windows of opportunity and first-mover advantages.

Key principles:
- **Actor-based thinking**: Model specific competitors and their capabilities
- **Publication signals**: Use publication patterns to predict future directions
- **Time windows**: Identify windows of opportunity that may close
- **Preemption risk**: Assess probability of being scooped or rendered redundant

## Execution Flow

1. **Identify competitive drivers** → spawn `scenario-driver-identification`
   - Input: research field, known competitors, publication landscape
   - Output: competitive uncertainty drivers

2. **Predict competitor moves** → spawn `competitive-move-prediction` (×3-5 competitors)
   - Input: competitor profile, publication history, resource level
   - Output: predicted actions and timelines per competitor

3. **Project timelines** → spawn `timeline-projection`
   - Input: competitor predictions, technology maturity
   - Output: competitive timeline with key milestones

4. **Assess impact** → spawn `scenario-impact-assessment` (per competitive scenario)
   - Input: competitive scenario, our research approach
   - Output: positioning impact, window analysis

5. **Score robustness** → spawn `robustness-scoring`
   - Input: all competitive assessments
   - Output: competitive robustness index

6. **Synthesize** → spawn `scenario-synthesis`
   - Input: competitive scenarios, timelines, robustness
   - Output: competitive strategy report

## Budget Gate

| Step | Token Budget | Notes |
|------|-------------|-------|
| Driver identification | 8K | Competitor-focused |
| Move prediction | 10K × N | N = 3-5 key competitors |
| Timeline projection | 12K | Multi-horizon |
| Impact assessment | 10K × N | Per competitive scenario |
| Robustness scoring | 8K | Competitive positioning |
| Synthesis | 12K | Strategy recommendations |

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## Available Tactics

Optional, no fixed order; the final leaf is always a sop.

| Tactic | When to use |
| --- | --- |
| strategy-robustness-testing | Orchestrates impact assessment and robustness scoring to evaluate research approach resilience across scenarios |

## Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use |
| --- | --- |
| competitive-move-prediction | Predict competitor progress, publications, and strategic moves |
| robustness-scoring | Compute robustness index across scenarios with sensitivity analysis |
| scenario-driver-identification | Identify key uncertainty drivers using PESTEL framework scanning |
| scenario-impact-assessment | Assess each scenario's impact on the research approach across multiple dimensions |
| scenario-synthesis | Comprehensive scenario analysis report synthesizing all scenario work |
| timeline-projection | Extrapolate research landscape timelines using trend analysis and milestone projection |

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