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evernote-performance-tuning

Optimize Evernote integration performance. Use when improving response times, reducing API calls, or scaling Evernote integrations. Trigger with phrases like "evernote performance", "optimize evernote", "evernote speed", "evernote caching".

Install with Tessl CLI

npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill evernote-performance-tuning
What are skills?

79

Does it follow best practices?

Validation for skill structure

SKILL.md
Review
Evals

Evaluation results

100%

25%

Build an Evernote API Caching Layer

Redis caching with TTLs and key patterns

Criteria
Without context
With context

ioredis library

100%

100%

Notebook TTL = 3600

100%

100%

Note metadata TTL = 300

0%

100%

Search TTL = 60

100%

100%

MD5 search key hashing

0%

100%

Key naming pattern

50%

100%

Note invalidation

100%

100%

User cache invalidation

100%

100%

Note full content caching

100%

100%

Redis quit on exit

100%

100%

Without context: $0.3367 · 1m 26s · 19 turns · 20 in / 5,387 out tokens

With context: $0.4859 · 1m 30s · 21 turns · 20 in / 5,344 out tokens

83%

58%

Optimize Evernote Note Retrieval for a Document Archive

Lazy resource loading and bulk note retrieval

Criteria
Without context
With context

Metadata-only fetch params

0%

100%

Bulk batch size = 5

0%

100%

100ms inter-batch delay

0%

100%

Bulk parallel within batch

50%

100%

Lazy resource loading

50%

100%

getResource params

0%

100%

Conditional caching logic

0%

0%

Async generator search

0%

100%

NoteFilter words property

50%

80%

NotesMetadataResultSpec fields

100%

50%

Without context: $0.3777 · 1m 42s · 18 turns · 19 in / 5,979 out tokens

With context: $0.5225 · 1m 47s · 24 turns · 23 in / 5,670 out tokens

100%

45%

Add Observability and Connection Management to Evernote API Gateway

Performance monitoring and connection management

Criteria
Without context
With context

Proxy instrumentation

100%

100%

Proxy wraps all methods

100%

100%

Required metrics tracked

20%

100%

Call records cap = 1000

0%

100%

p95 latency in getStats

0%

100%

cacheHitRate percentage

0%

100%

ConnectionManager client reuse

100%

100%

maxIdleTime = 5 minutes

100%

100%

RequestBatcher batchSize = 10

100%

100%

RequestBatcher batchDelay = 100

30%

100%

Without context: $0.4387 · 1m 42s · 23 turns · 24 in / 6,992 out tokens

With context: $0.5837 · 1m 47s · 27 turns · 58 in / 6,355 out tokens

Evaluated
Agent
Claude Code

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.