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Search autocomplete and type-ahead suggestion optimization for knowledge bases
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Showing SKILL.md
| name | autocomplete-engine |
| description | Search autocomplete and type-ahead suggestion optimization for knowledge bases |
| allowed-tools | ["Read","Write","Glob","Grep","Bash","WebFetch"] |
| metadata | {"specialization":"knowledge-management","domain":"business","category":"Search Optimization","skill-id":"SK-016"} |
| graph | {"domains":["domain:knowledge-management"],"skillAreas":["skill-area:search-indexing","skill-area:retrieval-augmented-generation","skill-area:natural-language-processing"],"roles":["role:information-architect","role:data-engineer","role:analytics-engineer"]} |
The Autocomplete Engine skill provides specialized capabilities for configuring, optimizing, and maintaining search autocomplete and type-ahead suggestion systems within knowledge management platforms. This skill enables intelligent, responsive search suggestions that improve user experience and reduce time-to-knowledge.
This skill primarily integrates with:
task: Configure autocomplete suggestion index
skill: autocomplete-engine
parameters:
platform: elasticsearch
index_name: knowledge-base-suggestions
config:
analyzer: standard
max_suggestions: 10
min_chars: 2
task: Analyze query logs for suggestion mining
skill: autocomplete-engine
parameters:
log_source: search-analytics
time_range: 30d
min_frequency: 10
output: suggestion-candidates.json
task: Configure personalized suggestions
skill: autocomplete-engine
parameters:
personalization:
user_history: true
role_based: true
recent_searches: 5
weight: 0.3
Key metrics to track for autocomplete optimization:
| Metric | Description | Target |
|---|---|---|
| Suggestion Latency | Time to return suggestions | < 100ms |
| Suggestion Acceptance Rate | % of searches using suggestions | > 40% |
| Position-1 Click Rate | % clicking first suggestion | > 25% |
| Zero-Suggest Rate | % queries with no suggestions | < 10% |
| Typo Recovery Rate | % typos successfully corrected | > 80% |