Nodejs Backend Patterns
ever-works/ever-works
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices.
Agent skill
by jeremylongshore in jeremylongshore/tons-of-skills-marketplace
Optimize Apollo.io API performance. An agent skill from jeremylongshore/tons-of-skills-marketplace.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill apollo-performance-tuning -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace apollo-performance-tuning --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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/apollo-performance-tuning .claude/skills/apollo-performance-tuning && rm -rf skills-srcUse ~/.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/
Install the "apollo-performance-tuning" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/apollo-performance-tuning into .claude/skills/apollo-performance-tuning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "apollo-performance-tuning", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/apollo-performance-tuningType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill apollo-performance-tuning -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace apollo-performance-tuning --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/.curated/apollo-performance-tuning .agents/skills/apollo-performance-tuning && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "apollo-performance-tuning" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/apollo-performance-tuning into .agents/skills/apollo-performance-tuning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "apollo-performance-tuning", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill apollo-performance-tuning -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace apollo-performance-tuning --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/.curated/apollo-performance-tuning .cursor/skills/apollo-performance-tuning && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "apollo-performance-tuning" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/apollo-performance-tuning into .cursor/skills/apollo-performance-tuning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "apollo-performance-tuning", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/jeremylongshore/tons-of-skills-marketplace.git --path skills/.curated/apollo-performance-tuning--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill apollo-performance-tuning -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace apollo-performance-tuning --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/.curated/apollo-performance-tuning .gemini/skills/apollo-performance-tuning && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "apollo-performance-tuning" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/apollo-performance-tuning into .gemini/skills/apollo-performance-tuning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "apollo-performance-tuning", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install jeremylongshore/tons-of-skills-marketplace apollo-performance-tuningInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill apollo-performance-tuning -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/.curated/apollo-performance-tuning .github/skills/apollo-performance-tuning && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "apollo-performance-tuning" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/apollo-performance-tuning into .github/skills/apollo-performance-tuning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "apollo-performance-tuning", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill apollo-performance-tuning -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace apollo-performance-tuning --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/.curated/apollo-performance-tuning .opencode/skills/apollo-performance-tuning && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "apollo-performance-tuning" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/apollo-performance-tuning into .opencode/skills/apollo-performance-tuning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "apollo-performance-tuning", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
apollo-performance-tuningOptimize Apollo.io API performance. An agent skill from jeremylongshore/tons-of-skills-marketplace.
Apollo Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Optimize Apollo.io API performance. Use when improving API response times, reducing latency, or optimizing bulk operations. Trigger with phrases like "apollo performance", "optimize apollo", "apollo slow", "apollo latency", "speed up apollo".
Its SKILL.md is about 2.1k 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 GraphQL. 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.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditBash(gh:*)Bash(curl:*)From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
api.apollo.ioAlso links to:
github.comdocs.apollo.ionodejs.orgFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
APOLLO_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Designed for Claude Code
From compatibility in the SKILL.md frontmatter.
Apollo Performance Tuning loads about 2.1k tokens when it runs, and up to ~4.4k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 313 words of instructions outside code blocks.
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.
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.
The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 313 words, ~2,064 tokens.
.claude/skills/apollo-performance-tuning/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Optimize Apollo.io API performance through response caching, connection pooling, bulk operations, parallel fetching, and result slimming. Key insight: search is free but slow (~500ms), enrichment costs credits — cache aggressively and batch enrichment calls.
Reuse TCP connections to avoid TLS handshake overhead on every request.
// src/apollo/optimized-client.ts
import axios from 'axios';
import https from 'https';
const httpsAgent = new https.Agent({
keepAlive: true,
maxSockets: 10,
maxFreeSockets: 5,
timeout: 30_000,
});
export const optimizedClient = axios.create({
baseURL: 'https://api.apollo.io/api/v1',
headers: { 'Content-Type': 'application/json', 'x-api-key': process.env.APOLLO_API_KEY! },
httpsAgent,
timeout: 15_000,
});// src/apollo/cache.ts
import { LRUCache } from 'lru-cache';
// Different TTLs based on data volatility
const CACHE_TTLS: Record<string, number> = {
'/organizations/enrich': 24 * 60 * 60 * 1000, // 24h — company data rarely changes
'/people/match': 4 * 60 * 60 * 1000, // 4h — contact data changes occasionally
'/mixed_people/api_search': 15 * 60 * 1000, // 15min — search results are dynamic
'/mixed_companies/search': 30 * 60 * 1000, // 30min — company search
'/contact_stages': 60 * 60 * 1000, // 1h — stages rarely change
};
const cache = new LRUCache<string, { data: any; at: number }>({
max: 5000,
maxSize: 50 * 1024 * 1024,
sizeCalculation: (v) => JSON.stringify(v).length,
});
function cacheKey(endpoint: string, params: any): string {
return `${endpoint}:${JSON.stringify(params)}`;
}
export async function cachedRequest<T>(
endpoint: string,
requestFn: () => Promise<T>,
params: any,
): Promise<T> {
const key = cacheKey(endpoint, params);
const ttl = CACHE_TTLS[endpoint] ?? 15 * 60 * 1000;
const cached = cache.get(key);
if (cached && Date.now() - cached.at < ttl) return cached.data;
const data = await requestFn();
cache.set(key, { data, at: Date.now() });
return data;
}
export function getCacheStats() {
return { entries: cache.size, sizeBytes: cache.calculatedSize };
}Apollo's bulk enrichment endpoint handles 10 records per call vs 1. Massive performance gain.
// src/apollo/bulk-ops.ts
import { optimizedClient } from './optimized-client';
import PQueue from 'p-queue';
const queue = new PQueue({ concurrency: 3, intervalCap: 2, interval: 1000 });
// Enrich 100 people: 100 individual calls = 100 requests @ 500ms = 50s
// Batch of 10: 10 bulk calls @ 600ms = 6s (8x faster, same credits)
export async function batchEnrich(
details: Array<{ email?: string; linkedin_url?: string; first_name?: string; last_name?: string; organization_domain?: string }>,
): Promise<any[]> {
const results: any[] = [];
for (let i = 0; i < details.length; i += 10) {
const batch = details.slice(i, i + 10);
const result = await queue.add(async () => {
const { data } = await optimizedClient.post('/people/bulk_match', {
details: batch,
reveal_personal_emails: false,
reveal_phone_number: false,
});
return data.matches ?? [];
});
results.push(...(result ?? []));
}
return results;
}export async function parallelSearch(
domains: string[],
concurrency: number = 5,
): Promise<Map<string, any[]>> {
const searchQueue = new PQueue({ concurrency });
const results = new Map<string, any[]>();
await searchQueue.addAll(
domains.map((domain) => async () => {
const data = await cachedRequest(
'/mixed_people/api_search',
() => optimizedClient.post('/mixed_people/api_search', {
q_organization_domains_list: [domain],
person_seniorities: ['vp', 'director', 'c_suite'],
per_page: 25,
}).then((r) => r.data),
{ domain },
);
results.set(domain, data.people ?? []);
}),
);
return results;
}Apollo returns large person objects (~2KB each). Extract only needed fields to reduce memory.
interface SlimPerson {
id: string;
name: string;
title: string;
email?: string;
company: string;
seniority: string;
}
function slimPerson(raw: any): SlimPerson {
return {
id: raw.id,
name: raw.name,
title: raw.title,
email: raw.email,
company: raw.organization?.name ?? '',
seniority: raw.seniority ?? '',
};
}
// Use immediately after API call to free memory
const { data } = await optimizedClient.post('/mixed_people/api_search', { ... });
const slim = data.people.map(slimPerson); // ~200 bytes each instead of ~2KBasync function benchmark(includePaidEndpoints = false) {
const endpoints = [
{ name: 'People Search', fn: () => optimizedClient.post('/mixed_people/api_search',
{ q_organization_domains_list: ['apollo.io'], per_page: 1 }) },
{ name: 'Auth Health', fn: () => optimizedClient.get('/auth/health') },
];
// Paid enrichment benchmarks require an approved, budgeted test run.
if (includePaidEndpoints) {
endpoints.push({ name: 'Org Enrich', fn: () => optimizedClient.get('/organizations/enrich',
{ params: { domain: 'apollo.io' } }) });
}
for (const ep of endpoints) {
const times: number[] = [];
for (let i = 0; i < 5; i++) {
const start = Date.now();
try { await ep.fn(); } catch {}
times.push(Date.now() - start);
}
const avg = Math.round(times.reduce((a, b) => a + b) / times.length);
const p95 = times.sort((a, b) => a - b)[Math.floor(times.length * 0.95)];
console.log(`${ep.name}: avg=${avg}ms, p95=${p95}ms`);
}
}keepAlive and configurable maxSockets/people/bulk_match (10x fewer requests)p-queue concurrency controlFor a search-latency regression, capture a baseline with the free search and health endpoints against a mock or approved sandbox fixture, then introduce connection reuse and a bounded cache behind a feature flag. Compare p95, error rate, cache-hit behavior, and result equivalence before promoting the change. A paid-enrichment benchmark requires an explicit approval flag, a fixed credit budget, and a public organization fixture; otherwise it remains out of the run. Roll back the flag if latency improves at the cost of stale, incorrect, or over-broadly cached results.
| Issue | Resolution |
|---|---|
| High latency | Enable connection pooling, check for stale cache |
| Cache misses | Increase TTL for stable data (org enrichment) |
| Rate limits with parallelism | Reduce p-queue concurrency |
| Memory growth | Lower LRU max entries, slim response payloads |
Proceed to apollo-cost-tuning for cost optimization.
© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in skills/.curated/apollo-performance-tuning of jeremylongshore/tons-of-skills-marketplace.
Open the folder on GitHubat commit cfae287
Apollo 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Apollo Performance Tuning this skilljeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~2.1k | Automated safety check: Pass | MIT | |
| Nodejs Backend Patternsever-works/ever-works | 162 | 18 repos | ~4k | Automated safety check: Pass | AGPL-3.0 | |
| API DesignerJeffallan/claude-skills | 12k | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| GraphQL Operations with CodegenChrisWiles/claude-code-showcase | 6.1k | 3 repos | ~1.5k | Automated safety check: Pass | None | |
| Supabasecurvenote/curvenote | 170 | 5 repos | ~2.2k | Automated safety check: Pass | Custom licence | |
| API Design Principlesjh941213/my-cc-harness | 125 | 18 repos | ~3.4k | Automated safety check: Pass | None |
ever-works/ever-works
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices.
Jeffallan/claude-skills
Designs REST and GraphQL APIs from resource modeling to an OpenAPI 3.1 contract, with versioning, pagination and RFC 7807 error handling.
ChrisWiles/claude-code-showcase
Sets the rules for writing GraphQL queries and mutations in .gql files, running codegen, and using generated Apollo hooks with proper error and loading handling.
curvenote/curvenote
A skill your agent uses when doing ANY task involving Supabase.
jh941213/my-cc-harness
REST 및 GraphQL API 설계 원칙 가이드. An agent skill from jh941213/my-cc-harness.
dzhalaevd/Donatello
Guides stable API and interface design. An agent skill from dzhalaevd/Donatello.
jeremylongshore/tons-of-skills-marketplace
Execute this skill enables AI assistant to conduct a security-focused code review using the security-agent plugin.
jeremylongshore/tons-of-skills-marketplace
Build this skill automates the adaptation of pre-trained machine learning models using transfer learning techniques.
jeremylongshore/tons-of-skills-marketplace
Execute proactive auto-loading: automatically detects and loads agents.md files.
jeremylongshore/tons-of-skills-marketplace
Aggregate and centralize performance metrics from applications, systems, databases, caches, and services.
jeremylongshore/tons-of-skills-marketplace
Execute this skill enables AI assistant to analyze capacity requirements and plan for future growth.
jeremylongshore/tons-of-skills-marketplace
Process use when you need to work with database indexing. An agent skill from jeremylongshore/tons-of-skills-marketplace.
Categories
Optimize Apollo.io API performance. An agent skill from jeremylongshore/tons-of-skills-marketplace. Apollo Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace.io API performance.
Apollo Performance Tuning fits situations like: improving API response times; reducing latency; optimizing bulk operations; with phrases like apollo performance.
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill apollo-performance-tuning -a claude-code`. Or copy the skill folder (skills/.curated/apollo-performance-tuning in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/apollo-performance-tuning in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill apollo-performance-tuning -a codex`. Or copy the skill folder (skills/.curated/apollo-performance-tuning in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/apollo-performance-tuning in your project. Codex loads it when a task matches its description.
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 apollo-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/apollo-performance-tuning, .gemini/skills/apollo-performance-tuning, .github/skills/apollo-performance-tuning and .opencode/skills/apollo-performance-tuning in your project.
Going by SKILL.md and its folder, Apollo Performance Tuning needs credentials named APOLLO_API_KEY. Our summary lists: Node.js; A credential in APOLLO_API_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(gh:*), Bash(curl:*). Compatibility (from SKILL.md): Designed for Claude Code.
SKILL.md names 4 domains. In commands or code: api.apollo.io; the agent is likely to contact it when it follows the instructions. As links in the text: github.com, docs.apollo.io and nodejs.org. This is read from the text; nothing was executed.
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.
Apollo 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.
About 2.1k tokens (SKILL.md is roughly 8.3k 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 2.3k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Apollo Performance Tuning: Nodejs Backend Patterns (ever-works/ever-works, 162 stars), API Designer (Jeffallan/claude-skills, 12k stars), GraphQL Operations with Codegen (ChrisWiles/claude-code-showcase, 6.1k stars) and Supabase (curvenote/curvenote, 170 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.