Deep Escalation

Escalate 'needs_review' records to a deep LLM tier with web search and budget gating.

Updated Apr 23, 2026
One-click install
npx skills add https://github.com/TrevorMann/AIDataCleansing --skill deep-escalation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Deep Escalation
Source: https://github.com/TrevorMann/AIDataCleansing/tree/main/skills/_common/deep_escalation
Command: npx skills add https://github.com/TrevorMann/AIDataCleansing --skill deep-escalation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill is designed to address records that remain in the 'needs_review' state after the deterministic and AI planning phases of a data cleaning pipeline.

Core Features & Use Cases

  • Deep-tier Escalation: Escalates records to the deep LLM tier for multi-round investigation with web search, addressing stuck records.
  • Web Search Evidence Reuse: Utilizes the record's prior web-search evidence to avoid redundant searches.
  • Flagging and Decision Logging: Logs flags and audit decisions on the record after escalation.
  • Budget-gated Execution: Ensures that the deep LLM tier is only used when necessary, based on budget and record status.

Quick Start

Escalate a record to the deep LLM tier for analysis using the 'deep_escalation' skill.

Frequently Asked Questions about Deep Escalation

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

FAQPage Schema
How do I escalate stuck records needing deep LLM analysis in a data cleaning pipeline?▼

Deep tier escalation moves 'needs_review' records into a multi-round LLM investigation with web search integration. It specifically targets records stuck after deterministic and AI planning phases of a data cleaning pipeline.

What is the best way to avoid redundant web searches during LLM record escalation?▼

Reusing prior web-search evidence stored on the record avoids redundant web searches during LLM record escalation. The deep tier investigation checks existing evidence first before initiating new external queries.

How does budget-gated execution work for deep tier LLM data cleaning?▼

Budget-gated execution for deep tier LLM data cleaning restricts multi-round investigation to run only when necessary based on allocated budget and record status. This prevents excessive API usage on records not requiring deep analysis.

How do I log audit decisions and flags after escalating records for deep analysis?▼

The deep tier LLM automatically logs audit decisions and flags directly onto the record after escalating records for deep analysis. This occurs once the multi-round investigation concludes and a final verdict is reached.

When should I not use deep LLM escalation for data cleaning?▼

You should not use deep LLM escalation for data cleaning if records have not passed through deterministic and AI planning phases, or if budget constraints cannot support multi-round investigations with web search integration.