This skill cleans event streams by using reputation scoring and content grouping to identify canonical records.

Install

mkdir -p .claude/skills/deduplication && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/6694" && unzip -o skill.zip -d .claude/skills/deduplication && rm skill.zip

Installs to .claude/skills/deduplication

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Event deduplication with canonical selection, reputation scoring, and hash-based grouping for multi-source data aggregation. Handles both ID-based and content-based deduplication.
179 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Perform ID-based deduplication
  • Execute content-based semantic grouping
  • Calculate reputation scores for sources
  • Select canonical records from duplicate groups
  • Track deduplication reduction metrics

How it works

It groups items by normalized content keys or IDs, then applies a scoring function based on source reputation to select the canonical version.

Inputs & outputs

You give it
Array of objects from multiple data sources
You get back
Deduplicated array with canonical selection and source attribution

When to use deduplication

  • Deduplicating user records from multiple sources
  • Cleaning event logs for data analysis
  • Removing redundant data entries in pipelines
  • Selecting the best canonical data points

About deduplication

Performs data cleaning by deduplicating event streams. It utilizes reputation scoring and content-based grouping to select canonical records from aggregated datasets.

Event deduplication with canonical selection, reputation scoring, and hash-based grouping for multi-source data aggregation. Handles both ID-based and content-based deduplication.

When not to use it

  • When data requires complex fuzzy matching beyond simple normalization
  • When source reputation is not a relevant factor

Prerequisites

TypeScript environment

Limitations

  • Relies on predefined source reputation tiers
  • Normalization logic is limited to title and date

How it compares

It moves beyond simple URL-based filtering by using semantic normalization and reputation-weighted selection to preserve high-quality data.

Compared to similar skills

deduplication side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
deduplication (this skill)16moNo flagsIntermediate
data-engineering137moReviewAdvanced
crawl4ai218moReviewIntermediate
data-cleaning-pipeline135moReviewIntermediate

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Example prompts that trigger this skill in your AI assistant.

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