dry-consolidation

What it does

This skill enables AI agents to perform dry consolidation, a technique for merging multiple text sources or responses into a single, coherent summary without executing any external actions or side effects. It helps streamline information processing by reducing redundancy while preserving key details from the input data.

When to use it

• Synthesizing research notes: Combine fragmented findings from multiple documents into one unified report before taking action.
• De-duplicating conversation history: Merge repetitive updates from an ongoing chat thread to create a concise status overview.
• Pre-action verification: Generate a clean summary of proposed steps or data points before triggering execution workflows.
• Cross-referencing outputs: Align results from different AI tools into a single narrative for human review.

Key capabilities

• Merges multiple text inputs into one cohesive output
• Removes redundancy while retaining essential information
• Operates without executing external commands or side effects
• Maintains context across disparate source materials

Example prompts

• "Use dry-consolidation to merge these three project update emails into a single summary."
• "Dry consolidate the following code review comments and pull request descriptions into one clear feedback list."
• "Combine the outputs from my last three research queries about climate policy into a unified briefing."

Tips & gotchas

Ensure all input sources are complete and contextually aligned before consolidation to avoid losing nuance. This skill is purely text-based; it does not trigger any external actions or modify files directly.