Agent skill

Lokalise Performance Tuning

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

Optimize Lokalise API performance with caching, pagination, and bulk operations.

MITAuto-check passedBackend & APIs

Install Lokalise Performance Tuning

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

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace lokalise-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/lokalise-performance-tuning .claude/skills/lokalise-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
lokalise-performance-tuning
GitHub stars
2.8k
Token cost
~3.4k tokens
SKILL.md length
518 words
Files
1
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Optimize Lokalise API performance with caching, pagination, and bulk operations.

  • Works in 7 steps: Use Cursor Pagination for Large Datasets → Cache Translation Downloads Locally → Batch Key Operations → …
  • Experiencing slow API responses
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 4 more sections
  • Calls curl and jq; reaches api.lokalise.com; needs LOKALISE_API_TOKEN

What it does

Lokalise Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Optimize Lokalise API performance with caching, pagination, and bulk operations. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Lokalise integrations. Trigger with phrases like "lokalise performance", "optimize lokalise", "lokalise latency", "lokalise caching", "lokalise slow", "lokalise batch".

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Designed for Claude Code

It sits in Backend & APIs, covering Caching. 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

  • Experiencing slow API responses
  • Implementing caching strategies
  • Optimizing request throughput for Lokalise integrations
  • With phrases like lokalise performance

Example prompts

  • “lokalise performance”
  • “optimize lokalise”
  • “lokalise latency”
  • “/lokalise-performance-tuning”

Requirements

  • A credential in LOKALISE_API_TOKEN
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(npm:*), Bash(node:*), Bash(curl:*), Bash(jq:*), Grep

Workflow steps

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

  1. Use Cursor Pagination for Large Datasets
  2. Cache Translation Downloads Locally
  3. Batch Key Operations
  4. Implement Request Throttling
  5. Async File Operations with Webhooks
  6. Selective Language Downloads (Delta Exports)
  7. Measure and Benchmark

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
    • Bash(npm:*)
    • Bash(node:*)
    • Bash(curl:*)
    • Bash(jq:*)
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • curl
    • jq

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.lokalise.com

    Also links to:

    • developers.lokalise.com
    • npmjs.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • LOKALISE_API_TOKEN

    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

Lokalise Performance Tuning loads about 3.4k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 518 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k

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). 518 words, ~3,436 tokens.

Download SKILL.mdSave it as .claude/skills/lokalise-performance-tuning/SKILL.md (or your agent's skills folder).
name
lokalise-performance-tuning
description
Optimize Lokalise API performance with caching, pagination, and bulk operations. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Lokalise integrations. Trigger with phrases like "lokalise performance", "optimize lokalise", "lokalise latency", "lokalise caching", "lokalise slow", "lokalise batch".
allowed-tools
Read, Write, Edit, Bash(npm:*), Bash(node:*), Bash(curl:*), Bash(jq:*), Grep
compatibility
Designed for Claude Code
version
1.14.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, lokalise, api, performance

Lokalise Performance Tuning

Overview

Optimize Lokalise API throughput for translation pipelines by implementing cursor pagination, local caching, batch key operations (500/request), request throttling under the 6 req/s rate limit, and selective language downloads.

Prerequisites

  • @lokalise/node-api SDK v9+ (ESM) or REST API access
  • LOKALISE_API_TOKEN environment variable set
  • Understanding of project size (key count, language count) to calibrate batch sizes
  • Optional: Redis or LRU cache library for persistent caching

Instructions

Step 1: Use Cursor Pagination for Large Datasets

Cursor pagination is significantly faster than offset pagination for projects with 5K+ keys. Offset pagination degrades as page numbers increase because the server must skip rows; cursor pagination uses a pointer.

typescript
import { LokaliseApi } from '@lokalise/node-api';
const lok = new LokaliseApi({ apiKey: process.env.LOKALISE_API_TOKEN! });

// Generator that yields all keys using cursor pagination
async function* getAllKeys(projectId: string) {
  let cursor: string | undefined;
  do {
    const result = await lok.keys().list({
      project_id: projectId,
      limit: 500,              // Maximum allowed per request
      pagination: 'cursor',
      cursor,
    });
    for (const key of result.items) yield key;
    cursor = result.hasNextCursor() ? result.nextCursor : undefined;
  } while (cursor);
}

// Usage: 10,000 keys = 20 API calls (vs 100 with default limit=100)
let count = 0;
for await (const key of getAllKeys('PROJECT_ID')) {
  count++;
}
console.log(`Fetched ${count} keys`);

Offset pagination comparison (avoid for large projects):

KeysOffset (limit=100)Cursor (limit=500)Time saved
1,00010 requests2 requests80%
10,000100 requests20 requests80%
50,000500 requests (~84s)100 requests (~17s)80%
Step 2: Cache Translation Downloads Locally

Translation file downloads are the most expensive Lokalise operation. Cache them locally and use project last_activity timestamps to invalidate.

typescript
import { LokaliseApi } from '@lokalise/node-api';
import { readFileSync, writeFileSync, existsSync, mkdirSync } from 'fs';

const lok = new LokaliseApi({ apiKey: process.env.LOKALISE_API_TOKEN! });
const CACHE_DIR = '.lokalise-cache';

interface CacheEntry {
  url: string;
  timestamp: string;
  languages: string[];
}

function getCachePath(projectId: string, langIso: string): string {
  return `${CACHE_DIR}/${projectId}/${langIso}.json`;
}

function getMetaPath(projectId: string): string {
  return `${CACHE_DIR}/${projectId}/meta.json`;
}

async function downloadWithCache(projectId: string, langIso: string, format = 'json') {
  mkdirSync(`${CACHE_DIR}/${projectId}`, { recursive: true });
  const cachePath = getCachePath(projectId, langIso);
  const metaPath = getMetaPath(projectId);

  // Check if project was modified since last cache
  const project = await lok.projects().get(projectId);
  const lastActivity = project.statistics?.last_activity ?? project.created_at;

  if (existsSync(metaPath)) {
    const meta: CacheEntry = JSON.parse(readFileSync(metaPath, 'utf8'));
    if (meta.timestamp === lastActivity && existsSync(cachePath)) {
      console.log(`Cache hit: ${langIso} (unchanged since ${lastActivity})`);
      return JSON.parse(readFileSync(cachePath, 'utf8'));
    }
  }

  // Cache miss — download fresh
  const bundle = await lok.files().download(projectId, {
    format,
    filter_langs: [langIso],
    original_filenames: false,
  });

  // bundle.bundle_url contains a temporary download URL
  const response = await fetch(bundle.bundle_url);
  const data = await response.arrayBuffer();

  writeFileSync(cachePath, Buffer.from(data));
  writeFileSync(metaPath, JSON.stringify({
    url: bundle.bundle_url,
    timestamp: lastActivity,
    languages: [langIso],
  }));

  console.log(`Cache miss: downloaded ${langIso} (${data.byteLength} bytes)`);
  return data;
}
Step 3: Batch Key Operations

Lokalise supports creating, updating, and deleting up to 500 keys per request. Always batch instead of making individual requests.

typescript
// Bulk create keys — 500 per batch with rate limit awareness
async function createKeysBatched(projectId: string, keys: any[]) {
  const BATCH_SIZE = 500;
  const results = [];

  for (let i = 0; i < keys.length; i += BATCH_SIZE) {
    const batch = keys.slice(i, i + BATCH_SIZE);
    const result = await lok.keys().create({
      project_id: projectId,
      keys: batch,
    });
    results.push(...result.items);
    console.log(`Batch ${Math.floor(i / BATCH_SIZE) + 1}: created ${result.items.length} keys`);
    await new Promise(r => setTimeout(r, 200)); // Stay under 6 req/s
  }

  return results;
}

// Bulk update keys — same 500-key batch limit
async function updateKeysBatched(projectId: string, updates: Array<{key_id: number; [k: string]: any}>) {
  const BATCH_SIZE = 500;
  for (let i = 0; i < updates.length; i += BATCH_SIZE) {
    const batch = updates.slice(i, i + BATCH_SIZE);
    await lok.keys().bulk_update({
      project_id: projectId,
      keys: batch,
    });
    await new Promise(r => setTimeout(r, 200));
  }
}

// Bulk delete — up to 500 key IDs per request
async function deleteKeysBatched(projectId: string, keyIds: number[]) {
  const BATCH_SIZE = 500;
  for (let i = 0; i < keyIds.length; i += BATCH_SIZE) {
    const batch = keyIds.slice(i, i + BATCH_SIZE);
    await lok.keys().bulk_delete({
      project_id: projectId,
      keys: batch,
    });
    await new Promise(r => setTimeout(r, 200));
  }
}

// 2,000 keys: 4 batched requests instead of 2,000 individual ones
Step 4: Implement Request Throttling

A proper request queue prevents 429 Too Many Requests errors and makes your integration resilient under load.

typescript
import PQueue from 'p-queue';

// Lokalise rate limit: 6 requests/second
// Use 5 concurrent with 1s interval for safety margin
const queue = new PQueue({
  concurrency: 5,
  interval: 1000,
  intervalCap: 5,
});

async function throttledRequest<T>(fn: () => Promise<T>): Promise<T> {
  return queue.add(fn) as Promise<T>;
}

// All API calls go through the queue automatically
const project = await throttledRequest(() => lok.projects().get(projectId));
const keys = await throttledRequest(() => lok.keys().list({
  project_id: projectId,
  limit: 500,
  pagination: 'cursor',
}));

// Works for parallel operations too — queue enforces the rate limit
const projectIds = ['PROJ_1', 'PROJ_2', 'PROJ_3', 'PROJ_4', 'PROJ_5'];
const allProjects = await Promise.all(
  projectIds.map(id => throttledRequest(() => lok.projects().get(id)))
);
Step 5: Async File Operations with Webhooks

File uploads and downloads are processed asynchronously by Lokalise. Instead of polling the process status endpoint, use webhooks to get notified when processing completes.

bash
set -euo pipefail
# Set up a webhook for file operation events
curl -s -X POST "https://api.lokalise.com/api2/projects/${PROJECT_ID}/webhooks" \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://hooks.company.com/lokalise",
    "events": [
      "project.imported",
      "project.exported",
      "project.keys_added"
    ]
  }' | jq '{webhook_id: .webhook.webhook_id, url: .webhook.url, events: .webhook.events}'

If you must poll (no webhook endpoint available):

typescript
async function waitForProcess(projectId: string, processId: string, timeoutMs = 120_000) {
  const start = Date.now();
  while (Date.now() - start < timeoutMs) {
    const proc = await throttledRequest(() =>
      lok.queuedProcesses().get(projectId, processId)
    );
    if (proc.status === 'finished') return proc;
    if (proc.status === 'cancelled' || proc.status === 'failed') {
      throw new Error(`Process ${processId} ${proc.status}: ${proc.message}`);
    }
    await new Promise(r => setTimeout(r, 2000)); // Poll every 2s
  }
  throw new Error(`Process ${processId} timed out after ${timeoutMs}ms`);
}
Step 6: Selective Language Downloads (Delta Exports)

Downloading all languages when you only need one wastes bandwidth and API time. Always filter by language and, when possible, by modification timestamp.

typescript
// Download only changed translations since last sync
async function downloadDelta(projectId: string, langIso: string, sinceTimestamp: string) {
  // Filter keys modified after the given timestamp
  const keys = await lok.keys().list({
    project_id: projectId,
    limit: 500,
    pagination: 'cursor',
    filter_translation_lang_ids: langIso,
    // Unfortunately, Lokalise doesn't support filter_modified_after on keys endpoint.
    // Workaround: download full file and diff locally, or use webhooks for real-time sync.
  });

  return keys.items;
}

// Download a single language file instead of all languages
async function downloadSingleLanguage(projectId: string, langIso: string) {
  const result = await lok.files().download(projectId, {
    format: 'json',
    filter_langs: [langIso],        // Only this language
    original_filenames: false,       // Flat structure
    bundle_structure: '%LANG_ISO%.%FORMAT%', // e.g., fr.json
    export_empty_as: 'base',         // Fall back to base language for untranslated
    include_tags: ['production'],    // Only production-tagged keys
  });
  return result.bundle_url;
}
Step 7: Measure and Benchmark
bash
set -euo pipefail
# Benchmark API response times across endpoints
echo "=== Lokalise API Benchmarks ==="

echo -n "Projects list: "
curl -s -o /dev/null -w "%{time_total}s" \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  "https://api.lokalise.com/api2/projects?limit=10"
echo ""

echo -n "Keys list (limit=500): "
curl -s -o /dev/null -w "%{time_total}s" \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  "https://api.lokalise.com/api2/projects/${PROJECT_ID}/keys?limit=500"
echo ""

echo -n "File download trigger: "
curl -s -o /dev/null -w "%{time_total}s" \
  -X POST -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  -H "Content-Type: application/json" \
  "https://api.lokalise.com/api2/projects/${PROJECT_ID}/files/download" \
  -d '{"format":"json","filter_langs":["en"],"original_filenames":false}'
echo ""

echo -n "Rate limit headers: "
curl -s -D - -o /dev/null \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  "https://api.lokalise.com/api2/projects?limit=1" \
  | grep -i x-ratelimit
Show full SKILL.md (232 more words)Show less

Output

  • Cursor pagination implemented for all list operations (80% fewer API calls)
  • Translation download cache with timestamp-based invalidation
  • Batch key operations (create/update/delete) using 500-key batches
  • Request queue with PQueue throttling at 5 req/s (safety margin under 6 req/s limit)
  • Webhooks configured for async file operations (replacing polling)
  • Selective language downloads reducing bandwidth and processing time
  • Benchmark results for baseline performance measurement

Error Handling

IssueCauseSolution
429 Too Many RequestsExceeded 6 req/s global rate limitUse PQueue throttling (Step 4), retry with exponential backoff
Slow file downloadsLarge project with 50+ languagesFilter by filter_langs to download one language at a time
Pagination timeoutOffset pagination on 50K+ key projectsSwitch to cursor pagination (Step 1)
Bulk create partial failureNetwork timeout on large batchReduce batch size from 500 to 200 and add retry logic per batch
Cache stale after team editslast_activity not granular enoughReduce cache TTL or use webhooks to invalidate on project.translation_updated
bundle_url expiredDownload URL only valid for ~30 minutesFetch the URL and download immediately; do not store URLs for later

Examples

Quick Rate Limit Check
bash
set -euo pipefail
# See how much rate limit headroom you have right now
curl -s -D - -o /dev/null \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  "https://api.lokalise.com/api2/system/languages?limit=1" 2>/dev/null \
  | grep -iE 'x-ratelimit' | while read -r line; do echo "  $line"; done

Resources

Next Steps

  • For debugging performance issues, collect diagnostics with lokalise-debug-bundle.
  • For SDK upgrade to get latest pagination improvements, see lokalise-upgrade-migration.
  • For setting up CI pipelines with optimized API usage, see lokalise-ci-integration.

© 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

Just SKILL.md in skills/.curated/lokalise-performance-tuning of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287

Compare with similar skills

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Categories

Questions about Lokalise Performance Tuning

What does Lokalise Performance Tuning do?

Optimize Lokalise API performance with caching, pagination, and bulk operations. Lokalise Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Optimize Lokalise API performance with caching, pagination, and bulk operations.

When should I use Lokalise Performance Tuning?

Lokalise Performance Tuning fits situations like: experiencing slow API responses; implementing caching strategies; optimizing request throughput for Lokalise integrations; with phrases like lokalise performance.

How do I install Lokalise Performance Tuning in Claude Code?

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

How do I install Lokalise Performance Tuning in Codex?

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

Can I use Lokalise 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 lokalise-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/lokalise-performance-tuning, .gemini/skills/lokalise-performance-tuning, .github/skills/lokalise-performance-tuning and .opencode/skills/lokalise-performance-tuning in your project.

What does Lokalise Performance Tuning need to run?

Going by SKILL.md and its folder, Lokalise Performance Tuning needs the command-line tools its instructions call (curl and jq) and credentials named LOKALISE_API_TOKEN. Our summary lists: A credential in LOKALISE_API_TOKEN. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(npm:*), Bash(node:*), Bash(curl:*), Bash(jq:*), Grep. Compatibility (from SKILL.md): Designed for Claude Code.

Does Lokalise Performance Tuning access the network?

SKILL.md names 3 domains. In commands or code: api.lokalise.com; the agent is likely to contact it when it follows the instructions. As links in the text: developers.lokalise.com and npmjs.com. This is read from the text; nothing was executed.

Is Lokalise 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 Lokalise Performance Tuning use?

Lokalise 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 Lokalise Performance Tuning use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Lokalise Performance Tuning?

Skills that share tags, products or a category with Lokalise Performance Tuning: Stripe Projects (fossasia/eventyay, 1.7k stars), Foundatio (FoundatioFx/Foundatio, 2.1k stars), Wp Block Themes (gambitph/Stackable, 351 stars) and Wp Performance (gambitph/Stackable, 351 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Lokalise 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.