mit einem Klick
output-dev-http-client-create
// Create shared HTTP clients in src/shared/clients/ for Output SDK workflows. Use when integrating external APIs, creating service wrappers, or standardizing HTTP operations.
// Create shared HTTP clients in src/shared/clients/ for Output SDK workflows. Use when integrating external APIs, creating service wrappers, or standardizing HTTP operations.
Implement an Output SDK workflow from a plan document. Use when the user asks to build, implement, or code a workflow from an existing plan, or after output-plan-workflow has produced a plan and the user is ready to build.
Create offline evaluation tests for Output SDK workflows using @outputai/evals. Use when implementing test evaluators with verify(), creating dataset YAML files, building eval workflows, or running workflow tests via CLI.
Pick the right LLM model for an Output SDK prompt file. Use when writing a new .prompt file, reviewing a model choice, or upgrading a stale model. Walks through priority (reasoning/balance/speed/cost), provider selection, and a live lookup against the Vercel AI Gateway model index.
Create .prompt files for LLM operations in Output SDK workflows. Use when designing prompts, configuring LLM providers, or using Liquid.js templating.
Create .md skill files for Output framework's lazy-loaded instruction system. Use when adding skills to prompts, configuring skill loading, or debugging skill resolution.
Bulk-upgrade the model field across .prompt files to the latest version of each prompt's existing family. Use when prompt models have drifted (eg sonnet-4 → sonnet-4-6), after a long pause between framework updates, or as part of a periodic model-freshness pass. Within-family only — never changes provider or tier.
| name | output-dev-http-client-create |
| description | Create shared HTTP clients in src/shared/clients/ for Output SDK workflows. Use when integrating external APIs, creating service wrappers, or standardizing HTTP operations. |
| allowed-tools | ["Read","Write","Edit","Glob"] |
This skill documents how to create shared HTTP clients for Output SDK workflows. Clients are stored in src/shared/clients/ and shared across all workflows to ensure consistent error handling, retry logic, and API integration patterns.
HTTP clients are stored in the shared clients folder:
src/shared/clients/
├── gemini_client.ts # Google Gemini API client
├── jina_client.ts # Jina AI client
├── perplexity_client.ts # Perplexity API client
└── {service}_client.ts # Your new client
Important: Clients are shared across ALL workflows. Do NOT create per-workflow HTTP clients.
src/shared/
├── clients/ # API clients (this skill)
├── utils/ # Utility functions & helpers
├── services/ # Business logic services
├── steps/ # Shared step definitions (optional)
└── evaluators/ # Shared evaluators (optional)
Use relative imports from workflow files to shared clients:
// CORRECT - Relative path from workflow steps.ts
import { GeminiImageService } from '../../shared/clients/gemini_client.js';
import { parseResumeWithJina } from '../../shared/clients/jina_client.js';
// From shared steps (if used)
import { JinaClient } from '../clients/jina_client.js';
// CORRECT - Use @outputai/http wrapper
import { httpClient } from '@outputai/http';
// WRONG - Never use axios directly
import axios from 'axios';
// CORRECT - Import error types from @outputai/core
import { FatalError, ValidationError } from '@outputai/core';
// WRONG - Custom error classes
class MyCustomError extends Error { ... }
// CORRECT - Use @outputai/credentials for secrets
import { credentials } from '@outputai/credentials';
const apiKey = credentials.require('service.api_key');
// WRONG - Never use process.env for secrets
const apiKey = process.env.SERVICE_API_KEY;
import { FatalError, ValidationError } from '@outputai/core';
import { httpClient } from '@outputai/http';
import { credentials } from '@outputai/credentials';
const API_KEY = credentials.require('service.api_key');
const BASE_URL = 'https://api.service.com';
const serviceClient = httpClient({
prefixUrl: BASE_URL,
headers: {
Authorization: `Bearer ${API_KEY}`,
Accept: 'application/json'
},
timeout: 30000,
retry: {
limit: 3,
statusCodes: [408, 429, 500, 502, 503, 504]
}
});
/**
* Fetch data from the service
*
* @param query - Search query string
* @returns Processed response data
* @throws {FatalError} If authentication fails or resource not found
* @throws {ValidationError} If temporary error occurs
*/
export async function fetchServiceData(query: string): Promise<ServiceResponse> {
const response = await serviceClient.get('endpoint', {
searchParams: { q: query }
});
const data = await response.json();
if (!data.results) {
throw new FatalError('No results returned from service');
}
return data;
}
import { FatalError, ValidationError } from '@outputai/core';
import { httpClient } from '@outputai/http';
export interface ServiceOptions {
model?: string;
timeout?: number;
}
export class ServiceClient {
private readonly client: ReturnType<typeof httpClient>;
private readonly model: string;
constructor(apiKey?: string) {
const key = apiKey ?? credentials.require('service.api_key');
this.client = httpClient({
prefixUrl: 'https://api.service.com',
headers: {
Authorization: `Bearer ${key}`,
'Content-Type': 'application/json'
},
timeout: 30000,
retry: {
limit: 3,
statusCodes: [408, 429, 500, 502, 503, 504]
}
});
this.model = 'default-model';
}
async process(input: ProcessInput): Promise<ProcessOutput> {
try {
const response = await this.client.post('process', {
json: {
model: this.model,
input
}
});
return await response.json();
} catch (error: unknown) {
const err = error as { status?: number; message?: string };
if (err.status === 429) {
throw new ValidationError(`Rate limit exceeded: ${err.message}`);
}
if (err.status === 401 || err.status === 403) {
throw new FatalError(`Authentication failed: ${err.message}`);
}
throw new ValidationError(`Service call failed: ${err.message}`);
}
}
}
import { FatalError } from '@outputai/core';
import { httpClient } from '@outputai/http';
const JINA_API_KEY = process.env.JINA_API_KEY || '';
const JINA_BASE_URL = 'https://r.jina.ai';
const jinaClient = httpClient({
prefixUrl: JINA_BASE_URL,
headers: {
Authorization: `Bearer ${JINA_API_KEY}`,
Accept: 'application/json'
},
timeout: 30000,
retry: {
limit: 3,
statusCodes: [408, 413, 429, 500, 502, 503, 504]
}
});
/**
* Parse PDF resume using Jina Reader API
*/
export async function parseResumeWithJina(base64Pdf: string): Promise<string> {
const response = await jinaClient.post('', {
json: { pdf: base64Pdf },
headers: {
'Content-Type': 'application/json'
}
});
const data: {
data: {
content: string;
title?: string;
};
} = await response.json();
if (!data.data?.content) {
throw new FatalError('No content returned from Jina PDF parser');
}
return data.data.content;
}
/**
* Scrape text content from URL using Jina Reader
*/
export async function scrapeTextWithJina(url: string): Promise<string> {
const response = await jinaClient.get(url, {
headers: {
'X-Return-Format': 'text',
'X-No-Cache': 'true',
'X-Timeout': '30'
}
});
const data: {
data: {
text?: string;
content?: string;
};
} = await response.json();
const textContent = data.data?.text || data.data?.content;
if (!textContent) {
throw new FatalError(`No text content returned from URL: ${url}`);
}
return textContent;
}
import { GoogleGenerativeAI } from '@google/generative-ai';
import { FatalError, ValidationError } from '@outputai/core';
export interface GeminiImageGenerationOptions {
prompt: string;
referenceImages?: Array<{
inlineData: {
mimeType: string;
data: string;
};
}>;
aspectRatio?: string;
resolution?: string;
numberOfImages?: number;
}
export class GeminiImageService {
private readonly client: GoogleGenerativeAI;
// current as of 2026-05-04 — run output-dev-model-selection for the latest
private readonly model: string = 'gemini-3-pro-image';
constructor(apiKey = process.env.GOOGLE_GEMINI_API_KEY || process.env.GOOGLE_CLOUD_API_KEY) {
if (!apiKey) {
throw new FatalError(
'GeminiImageService: No API Key provided (GOOGLE_GEMINI_API_KEY or GOOGLE_CLOUD_API_KEY).'
);
}
this.client = new GoogleGenerativeAI(apiKey);
}
async generateImage(options: GeminiImageGenerationOptions): Promise<string[]> {
const { prompt, referenceImages = [], aspectRatio = '1:1', resolution = '1K', numberOfImages = 1 } = options;
try {
const model = this.client.getGenerativeModel({ model: this.model });
const parts: Array<{ text: string } | { inlineData: { mimeType: string; data: string } }> = [];
if (referenceImages.length > 0) {
referenceImages.forEach(img => parts.push(img));
}
const finalPrompt = `${prompt}\n\nGenerate this as a ${aspectRatio} aspect ratio image at ${resolution} resolution.`;
parts.push({ text: finalPrompt });
const result = await model.generateContent({
contents: [{ role: 'user', parts }],
generationConfig: {
temperature: 1.0,
topP: 0.95,
candidateCount: numberOfImages,
maxOutputTokens: 8192
}
});
const images: string[] = [];
const candidates = result.response.candidates || [];
for (const candidate of candidates) {
if (candidate.content?.parts) {
for (const part of candidate.content.parts) {
if (part.inlineData?.data) {
images.push(part.inlineData.data);
}
}
}
}
if (images.length === 0) {
throw new ValidationError('No images were generated by Gemini');
}
return images;
} catch (error: unknown) {
const err = error as { status?: number; message?: string };
if (err.status === 429) {
throw new ValidationError(`Gemini rate limit exceeded: ${err.message}`);
}
if (err.status === 401 || err.status === 403) {
throw new FatalError(`Gemini authentication failed: ${err.message}`);
}
throw new ValidationError(`Gemini image generation failed: ${err.message}`);
}
}
}
const RETRY_STATUS_CODES = [408, 429, 500, 502, 503, 504];
const FATAL_STATUS_CODES = [401, 403, 404];
const client = httpClient({
retry: {
limit: 3,
statusCodes: RETRY_STATUS_CODES
},
hooks: {
beforeError: [
error => {
const status = error.response?.status;
const message = error.message;
if (status && FATAL_STATUS_CODES.includes(status)) {
throw new FatalError(`HTTP ${status} error: ${message}`);
}
throw new ValidationError(`HTTP request failed: ${message}`);
}
]
}
});
| Status Code | Error Type | Reason |
|---|---|---|
| 401, 403 | FatalError | Auth failures won't succeed on retry |
| 404 | FatalError | Resource doesn't exist |
| 408 | ValidationError | Timeout, may succeed on retry |
| 429 | ValidationError | Rate limit, will succeed after wait |
| 500+ | ValidationError | Server errors may be temporary |
Prefer @outputai/credentials over process.env for secrets management. See output-dev-credentials skill for details.
import { credentials } from '@outputai/credentials';
// credentials.require() throws MissingCredentialError if not found
const apiKey = credentials.require('service.api_key');
// credentials.get() returns undefined or default if not found
const region = credentials.get('aws.region', 'us-east-1');
/**
* Fetch user profile from external service
*
* @param userId - Unique user identifier
* @returns User profile data
* @throws {FatalError} If user not found or auth fails
* @throws {ValidationError} If temporary error occurs
*
* @example
* const profile = await fetchUserProfile('user-123');
*/
export async function fetchUserProfile(userId: string): Promise<UserProfile> {
// ...
}
// Standard timeout: 30 seconds
timeout: 30000
// Long-running operations: 60 seconds
timeout: 60000
// Export interfaces for consumers
export interface ServiceResponse {
data: {
id: string;
content: string;
};
metadata: {
processedAt: string;
};
}
src/shared/clients/ directory{service}_client.tshttpClient imported from @outputai/http (not axios)FatalError and ValidationError imported from @outputai/coreoutput-dev-step-function - Using clients in step functionsoutput-dev-evaluator-function - Using clients in evaluatorsoutput-dev-folder-structure - Understanding project layoutoutput-dev-credentials - Encrypted secrets managementoutput-error-http-client - Troubleshooting HTTP issuesoutput-error-try-catch - Proper error handling patterns