deduplication
Event deduplication with canonical selection, reputation scoring, and hash-based grouping for multi-source data aggregation. Handles both ID-based and content-based deduplication.
77
Quality
66%
Does it follow best practices?
Impact
98%
1.58xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/data-access/deduplication-dadbodgeoff-drift/SKILL.mdQuality
Discovery
67%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description excels at technical specificity and carves out a clear, distinctive niche for event deduplication workflows. However, it lacks explicit trigger guidance ('Use when...') and relies heavily on technical jargon that users may not naturally use when requesting help with duplicate data problems.
Suggestions
Add a 'Use when...' clause with explicit triggers, e.g., 'Use when the user needs to remove duplicate events, merge data from multiple sources, or identify canonical records.'
Include natural language variations users might say: 'remove duplicates', 'merge events', 'combine feeds', 'find duplicate records', 'dedupe data'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'canonical selection', 'reputation scoring', 'hash-based grouping', 'ID-based and content-based deduplication'. These are concrete technical operations, not vague abstractions. | 3 / 3 |
Completeness | Clearly answers 'what does this do' with specific capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The 'when' is only implied through the technical domain description. | 2 / 3 |
Trigger Term Quality | Contains relevant technical terms like 'deduplication', 'multi-source data aggregation', 'hash-based grouping', but lacks natural user language variations. Users might say 'remove duplicates', 'merge events', 'combine data sources' which aren't covered. | 2 / 3 |
Distinctiveness Conflict Risk | Highly specific niche combining 'event deduplication', 'canonical selection', 'reputation scoring', and 'multi-source data aggregation'. This combination is distinctive and unlikely to conflict with general data processing or document skills. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides solid, executable TypeScript implementations for event deduplication with good coverage of both ID-based and content-based approaches. However, it could be more concise by removing explanatory sections Claude doesn't need, and would benefit from explicit validation steps and better content organization across files.
Suggestions
Remove or significantly trim the 'Core Concepts' and 'When to Use This Skill' sections - Claude understands deduplication concepts
Add validation checkpoints: verify input array is non-empty, validate dedup key generation, confirm canonical selection worked correctly
Split the large implementation into separate referenced files (e.g., ID_BASED.md, CONTENT_BASED.md) with just the quick-start example inline
Make the reputation scoring configurable rather than hardcoded - or note this as a customization point more explicitly
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient but includes some unnecessary sections like 'Core Concepts' that explain things Claude already understands (what deduplication is, why simple URL dedup isn't enough). The 'When to Use This Skill' section is also somewhat redundant given the description. | 2 / 3 |
Actionability | Provides fully executable TypeScript code with complete implementations for both ID-based and content-based deduplication. Code is copy-paste ready with proper imports, type definitions, and usage examples. | 3 / 3 |
Workflow Clarity | The skill presents functions and usage examples but lacks explicit workflow sequencing for multi-step processes. No validation checkpoints are provided for verifying deduplication results or handling edge cases like empty inputs or malformed data. | 2 / 3 |
Progressive Disclosure | Content is reasonably structured with clear sections, but the implementation section is quite long (could be split into separate files for ID-based vs content-based). The 'Related Patterns' section references other files but the main content is monolithic. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
Total | 10 / 11 Passed | |
- Repository
- majiayu000/claude-skill-registry
- Commit
6213d1a
- Reviewed
Table of Contents
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