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Agent skill

Evernote Performance Tuning

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Optimize Evernote integration performance. An agent skill from jeremylongshore/tons-of-skills-marketplace.

MITAuto-check passedBackend & APIs

Install Evernote Performance Tuning

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill evernote-performance-tuning -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace evernote-performance-tuning --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/evernote-performance-tuning .claude/skills/evernote-performance-tuning && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
evernote-performance-tuning
GitHub stars
2.8k
Token cost
~1.1k tokens
SKILL.md length
367 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Optimize Evernote integration performance. An agent skill from jeremylongshore/tons-of-skills-marketplace.

  • Works in 5 steps: Response Caching → Efficient Data Retrieval → Request Batching → …
  • Improving response times
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Evernote Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. 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".

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/implementation-guide.md`). Compatibility notes: Designed for Claude Code

It sits in Backend & APIs, covering Caching. It works with Redis. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Improving response times
  • Reducing API calls
  • Scaling Evernote integrations
  • With phrases like evernote performance

Example prompts

  • “evernote performance”
  • “optimize evernote”
  • “evernote speed”
  • “/evernote-performance-tuning”

Requirements

  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Grep

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Response Caching
  2. Efficient Data Retrieval
  3. Request Batching
  4. Connection Optimization
  5. Performance Monitoring

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • dev.evernote.com
    • redis.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Evernote Performance Tuning loads about 1.1k tokens when it runs, and up to ~4.9k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 367 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 367 words, ~1,146 tokens.

Download SKILL.mdSave it as .claude/skills/evernote-performance-tuning/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
evernote-performance-tuning
description
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".
allowed-tools
Read, Write, Edit, Grep
compatibility
Designed for Claude Code
version
1.13.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, evernote, api, performance, scaling

Evernote Performance Tuning

Overview

Optimize Evernote API integration performance through response caching, efficient data retrieval, request batching, connection management, and performance monitoring.

Prerequisites

  • Working Evernote integration
  • Understanding of API rate limits
  • Caching infrastructure (Redis recommended, in-memory for simpler setups)

Instructions

Step 1: Response Caching

Cache frequently accessed data (notebook lists, tag lists, note metadata) with TTL-based expiration. Notebook and tag lists change rarely -- cache for 5-15 minutes. Note metadata can be cached for 1-5 minutes.

javascript
class EvernoteCache {
  constructor(redis) {
    this.redis = redis;
  }

  async getOrFetch(key, fetcher, ttlSeconds = 300) {
    const cached = await this.redis.get(key);
    if (cached) return JSON.parse(cached);

    const data = await fetcher();
    await this.redis.setex(key, ttlSeconds, JSON.stringify(data));
    return data;
  }

  async listNotebooks(noteStore) {
    return this.getOrFetch('notebooks', () => noteStore.listNotebooks(), 600);
  }

  async listTags(noteStore) {
    return this.getOrFetch('tags', () => noteStore.listTags(), 600);
  }
}
Step 2: Efficient Data Retrieval

Use findNotesMetadata() instead of findNotes() to avoid transferring full note content. Only request needed fields in NotesMetadataResultSpec. Fetch full content only when the user explicitly opens a note.

javascript
// BAD: Fetches full content for all notes
const notes = await noteStore.findNotes(filter, 0, 100);

// GOOD: Fetches only metadata (title, dates, tags)
const metadata = await noteStore.findNotesMetadata(filter, 0, 100, spec);
// Fetch content only for the specific note user opens
const fullNote = await noteStore.getNote(guid, true, false, false, false);
Step 3: Request Batching

Batch multiple operations using sync chunks instead of individual API calls. Use getSyncChunk() to fetch up to 100 changed notes in a single call instead of 100 getNote() calls.

Step 4: Connection Optimization

Reuse the Evernote client instance across requests. The NoteStore maintains an HTTP connection that benefits from keep-alive. Create one client per user session, not per request.

Step 5: Performance Monitoring

Track API call counts, response times (p50, p95, p99), cache hit rates, and rate limit occurrences. Alert on degradation.

For the complete caching layer, batching strategies, monitoring setup, and benchmark examples, see Implementation Guide.

Show full SKILL.md (158 more words)Show less

Output

  • Redis-based response caching with TTL management
  • Metadata-only query patterns (avoid unnecessary content transfer)
  • Sync chunk batching for bulk operations
  • Client instance reuse for connection optimization
  • Performance monitoring with latency percentiles and cache hit rates

Error Handling

ErrorCauseSolution
RATE_LIMIT_REACHEDToo many API callsIncrease cache TTL, batch operations
Stale cache dataCache not invalidated on updateInvalidate cache on webhook notification
Redis connection failureCache infrastructure downFall through to direct API call
Slow responsesLarge note content in responseUse findNotesMetadata() for listings

Resources

Next Steps

For cost optimization, see evernote-cost-tuning.

Examples

Cache notebook lookups: Cache listNotebooks() for 10 minutes. On 100 requests/minute, this reduces API calls from 100 to 1 per 10-minute window (99% reduction).

Lazy content loading: Show note titles from cached metadata. Fetch full ENML content only when user clicks to read. Reduces average response time from 500ms to 50ms for list views.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/evernote-performance-tuning of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/implementation-guide.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Evernote Performance Tuning next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Evernote Performance Tuning this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.1kAutomated safety check: PassMIT
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FoundatioFoundatioFx/Foundatio2.1k—~3.9kAutomated safety check: PassApache-2.0
FastAPI-Redis SDK Developmentredis/fastapi-redis-sdk405—~2.5kAutomated safety check: NotesMIT
Caching Patternsdilolabs/nosia2131 repos~1.9kAutomated safety check: PassMIT
Cachingcodewithmukesh/dotnet-claude-kit7561 repos~1.4kAutomated safety check: PassMIT

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Works with

Categories

Questions about Evernote Performance Tuning

What does Evernote Performance Tuning do?

Optimize Evernote integration performance. An agent skill from jeremylongshore/tons-of-skills-marketplace. Evernote Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Optimize Evernote integration performance.

When should I use Evernote Performance Tuning?

Evernote Performance Tuning fits situations like: improving response times; reducing API calls; scaling Evernote integrations; with phrases like evernote performance.

How do I install Evernote Performance Tuning in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill evernote-performance-tuning -a claude-code`. Or copy the skill folder (skills/.curated/evernote-performance-tuning in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/evernote-performance-tuning in your project. Claude Code loads it when a task matches its description.

How do I install Evernote Performance Tuning in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill evernote-performance-tuning -a codex`. Or copy the skill folder (skills/.curated/evernote-performance-tuning in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/evernote-performance-tuning in your project. Codex loads it when a task matches its description.

Can I use Evernote Performance Tuning in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill evernote-performance-tuning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/evernote-performance-tuning, .gemini/skills/evernote-performance-tuning, .github/skills/evernote-performance-tuning and .opencode/skills/evernote-performance-tuning in your project.

What does Evernote Performance Tuning need to run?

SKILL.md names no scripts, command-line tools or credentials: Evernote Performance Tuning is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep. Compatibility (from SKILL.md): Designed for Claude Code.

Does Evernote Performance Tuning access the network?

SKILL.md names 2 domains. As links in the text: dev.evernote.com and redis.io. This is read from the text; nothing was executed.

Is Evernote Performance Tuning safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Evernote Performance Tuning use?

Evernote Performance Tuning is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Evernote Performance Tuning use?

About 1.1k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.8k tokens, read only when the agent opens those files.

What are the alternatives to Evernote Performance Tuning?

Skills that share tags, products or a category with Evernote Performance Tuning: Stripe Projects (fossasia/eventyay, 1.7k stars), Foundatio (FoundatioFx/Foundatio, 2.1k stars), FastAPI-Redis SDK Development (redis/fastapi-redis-sdk, 405 stars) and Caching Patterns (dilolabs/nosia, 213 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Evernote Performance Tuning?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.