Agent skill · AI & Agents

stakeholder-preference-elicitor

Stakeholder preference elicitation skill for structured value and weight gathering

a5c-ai1,642★ · 1 repos on radarProfile →
claude-codecodexcan modify filesMIT
Install
npx skills add a5c-ai/babysitter --skill stakeholder-preference-elicitor --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 8 KB
Bundled scripts: none
Allowed tools: -Read-Write-Glob-Grep-Bash
Path: library/specializations/domains/business/decision-intelligence/skills/stakeholder-preference-elicitor/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,642
Language: JavaScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Stakeholder Preference Elicitor ## Overview The Stakeholder Preference Elicitor skill provides structured methods for gathering value judgments and weights from decision stakeholders. It supports multiple elicitation techniques, consistency checking, and preference aggregation for group decisions. ## Capabilities - Swing weight elicitation - Direct rating collection - Trade-off questioning - Consistency checking - Preference aggregation - Disagreement identification - Facilitation guidance - Preference documentation ## Used By Processes - Multi-Criteria Decision Analysis (MCDA) - Structured Decision Making Process - KPI Framework Development ## Usage ### Elicitation Session Setup ```python # Configure elicitation session session_config = { "decision": "Enterprise Software Selection", "criteria": [ {"name": "Total Cost of Ownership", "unit": "USD", "direction": "minimize"}, {"name": "Implementation Time", "unit": "months", "direction": "minimize"}, {"name": "Functionality Fit", "unit": "percent", "direction": "maximize"}, {"name": "Vendor Stability", "unit": "score", "direction": "maximize"}, {"name": "Integration Capability", "unit": "score", "direction": "maximize"} ], "stakehol

What's inside
Steps it walks through
  1. Overview
  2. Capabilities
  3. Used By Processes
  4. Usage
  5. Elicitation Session Setup
  6. Swing Weight Elicitation
  7. Trade-off Questions
  8. Consistency Check
  9. Group Aggregation
  10. Input Schema
  11. Output Schema
  12. Elicitation Methods
  13. Best Practices
  14. Common Biases
More from babysitter
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About this skill
What does the stakeholder-preference-elicitor skill do?

Stakeholder preference elicitation skill for structured value and weight gathering

How do I install it?

Run `npx skills add a5c-ai/babysitter --skill stakeholder-preference-elicitor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going