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conflict-data-guardrails

Enforce labeling of UCDP historical data versus VIEWS forecasts in outputs.

Updated Mar 3, 2026
Search Tags:#citations#uncertainty#views#guardrails#ucdp#conflict-data
One-click install
npx skills add https://github.com/BLANXLAIT/demscore-tools --skill conflict-data-guardrails
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: conflict-data-guardrails
Source: https://github.com/BLANXLAIT/demscore-tools/tree/main/packages/skill
Command: npx skills add https://github.com/BLANXLAIT/demscore-tools --skill conflict-data-guardrails

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

These guardrails enforce responsible presentation of conflict data from UCDP and VIEWS, ensuring clear separation between historical observations and forecasts, and providing safety rails for analysts and automated reports.

Core Features & Use Cases

  • Enforces strict labeling between historical UCDP data (observed) and VIEWS forecasts (probabilistic), including proper uncertainty handling and hedging.
  • Provides guidance on avoiding causal claims, ensuring data freshness citations, and supporting audit-friendly reporting.
  • Facilitates consistent deployment across MCP server workflows and SDK-integrated data pipelines, enabling repeatable governance for combined analyses.

Quick Start

Enable the guardrails in your MCP server workflow and validate all conflict-data outputs against the rules before publishing.

Frequently Asked Questions about conflict-data-guardrails

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prevent conflating historical conflict data with forecasts in automated reports?▼

You can separate historical UCDP observations from VIEWS forecasts by applying guardrails that enforce strict labeling and probabilistic uncertainty hedging in your MCP server workflows and SDK data pipelines.

What is the best way to ensure responsible presentation of UCDP conflict data?▼

The best way to ensure responsible presentation of UCDP conflict data is to validate outputs against guardrails that enforce proper citation rules, avoid causal claims, and maintain data freshness before publishing dashboards or reports.

Do I need the demscore-tools MCP server to apply conflict data guardrails?▼

Yes, these guardrails are designed to integrate with workflows using the demscore-tools MCP server and the @demscore/ucdp and @demscore/views SDKs to validate combined analyses and ensure governed data outputs.

How do I add uncertainty hedging to VIEWS forecast outputs in my dashboards?▼

You add uncertainty hedging to VIEWS forecast outputs by enabling guardrails in your workflow that enforce probabilistic labeling and validate all conflict-data outputs against responsible presentation rules before publishing.

Why does my combined UCDP and VIEWS analysis lack audit-friendly citations?▼

Your combined analysis lacks audit-friendly citations because guardrails enforcing data freshness, proper citation rules, and explicit separation of observed historical data from forecasts were not applied to the reporting pipeline.

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