Compare feasibility across multiple candidates using multi-dimensional radar and weighted feasibility index.
Scanned 6/1/2026
Install to Claude Code
npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill comparative-feasibility-ranking --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Comparative Feasibility Ranking?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/yogsoth-ai-comparative-feasibility-ranking)More formats (shields.io, HTML) on the badges page.
---
name: comparative-feasibility-ranking
description: Compare feasibility across multiple candidates using multi-dimensional radar and weighted feasibility index.
used-by: feasibility-assessment
---
# Comparative Feasibility Ranking
**Purpose:** Produce a defensible ranking of candidates by feasibility. Uses multi-dimensional radar charts to visualize relative strengths and a weighted feasibility index to collapse multiple dimensions into a single comparable score.
**When to use:**
- Multiple candidates have been assessed and need to be compared
- Stakeholders need a clear ranking to prioritize resource allocation
- You need to identify which candidates are most implementable given current constraints
## Budget
| Metric | Target |
|--------|--------|
| Candidates compared | >= 2 |
| Dimensions in radar | >= 5 |
| Weight justifications | 1 per dimension |
## State Ledger
| Key | Type | Description |
|-----|------|-------------|
| candidates[] | array | All candidates being compared |
| dimension_weights{} | map | Dimension -> weight mapping |
| radar_data[] | array | Per-candidate radar scores |
| feasibility_index[] | array | Weighted composite scores |
| ranking[] | array | Final ranked list |
## Available Tactics
| Tactic | When |
|--------|------|
| multi-dimensional-readiness-scan | To generate per-candidate radar data for comparison |
| staged-gate-evaluation | To compare gate-passage likelihood across candidates |
## Available SOPs
| SOP | Purpose |
|-----|---------|
| radar-synthesis | Produce radar data for each candidate |
| feasibility-synthesis | Produce final comparative matrix |
## Execution Guidance
1. Ensure all candidates have been assessed on the same dimensions
2. Normalize scores to a common scale (1-9 recommended)
3. Assign dimension weights based on context (stakeholder priorities, strategic fit)
4. Calculate weighted feasibility index for each candidate
5. Produce comparative radar visualization data
6. Rank candidates and identify clear tiers (strong/moderate/weak feasibility)
## Output Format
```yaml
comparative_ranking:
dimensions: [technical, market, regulatory, resource, organizational]
weights: {technical: 0.3, market: 0.25, regulatory: 0.2, resource: 0.15, organizational: 0.1}
candidates:
- {name, scores: {...}, weighted_index: 0.X, rank: N, tier: strong|moderate|weak}
radar_data: [{candidate, dimension_scores: [...]}]
recommendation: <top candidate(s) with rationale>
caveats: [...]
```
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!