소스 정보
- 저장소
- bouclem/skills
- 최근 소스 활동
- 2026년 5월 24일 16:04
- 감지된 SKILL.md 언어
- 영어
- 스타
- 7
- 포크
- 1
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/bouclem/skills --skill azure-ai-translation-ts명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.
12-agent academic paper writing pipeline. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見.
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | azure-ai-translation-ts |
| description | Text and document translation with REST-style clients. |
| risk | unknown |
| source | community |
| date_added | 2026-02-27 |
Text and document translation with REST-style clients.
# Text translation
npm install @azure-rest/ai-translation-text @azure/identity
# Document translation
npm install @azure-rest/ai-translation-document @azure/identity
TRANSLATOR_ENDPOINT=https://api.cognitive.microsofttranslator.com
TRANSLATOR_SUBSCRIPTION_KEY=<your-api-key>
TRANSLATOR_REGION=<your-region> # e.g., westus, eastus
import TextTranslationClient, { TranslatorCredential } from "@azure-rest/ai-translation-text";
// API Key + Region
const credential: TranslatorCredential = {
key: process.env.TRANSLATOR_SUBSCRIPTION_KEY!,
region: process.env.TRANSLATOR_REGION!,
};
const client = TextTranslationClient(process.env.TRANSLATOR_ENDPOINT!, credential);
// Or just credential (uses global endpoint)
const client2 = TextTranslationClient(credential);
import TextTranslationClient, { isUnexpected } from "@azure-rest/ai-translation-text";
const response = await client.path("/translate").post({
body: {
inputs: [
{
text: "Hello, how are you?",
language: "en", // source (optional, auto-detect)
targets: [
{ language: "es" },
{ language: "fr" },
],
},
],
},
});
if (isUnexpected(response)) {
throw response.body.error;
}
for (const result of response.body.value) {
for (const translation of result.translations) {
console.log(`${translation.language}: ${translation.text}`);
}
}
const response = await client.path("/translate").post({
body: {
inputs: [
{
text: "Hello world",
language: "en",
textType: "Plain", // or "Html"
targets: [
{
language: "de",
profanityAction: "NoAction", // "Marked" | "Deleted"
tone: "formal", // LLM-specific
},
],
},
],
},
});
const response = await client.path("/languages").get();
if (isUnexpected(response)) {
throw response.body.error;
}
// Translation languages
for (const [code, lang] of Object.entries(response.body.translation || {})) {
console.log(`${code}: ${lang.name} (${lang.nativeName})`);
}
const response = await client.path("/transliterate").post({
body: { inputs: [{ text: "这是个测试" }] },
queryParameters: {
language: "zh-Hans",
fromScript: "Hans",
toScript: "Latn",
},
});
if (!isUnexpected(response)) {
for (const t of response.body.value) {
console.log(`${t.script}: ${t.text}`); // Latn: zhè shì gè cè shì
}
}
const response = await client.path("/detect").post({
body: { inputs: [{ text: "Bonjour le monde" }] },
});
if (!isUnexpected(response)) {
for (const result of response.body.value) {
console.log(`Language: ${result.language}, Score: ${result.score}`);
}
}
import DocumentTranslationClient from "@azure-rest/ai-translation-document";
import { DefaultAzureCredential } from "@azure/identity";
const endpoint = "https://<translator>.cognitiveservices.azure.com";
// TokenCredential
const client = DocumentTranslationClient(endpoint, new DefaultAzureCredential());
// API Key
const client2 = DocumentTranslationClient(endpoint, { key: "<api-key>" });
import DocumentTranslationClient from "@azure-rest/ai-translation-document";
import { writeFile } from "node:fs/promises";
const response = await client.path("/document:translate").post({
queryParameters: {
targetLanguage: "es",
sourceLanguage: "en", // optional
},
contentType: "multipart/form-data",
body: [
{
name: "document",
body: "Hello, this is a test document.",
filename: "test.txt",
contentType: "text/plain",
},
],
}).asNodeStream();
if (response.status === "200") {
await writeFile("translated.txt", response.body);
}
import { ContainerSASPermissions, BlobServiceClient } from "@azure/storage-blob";
// Generate SAS URLs for source and target containers
const sourceSas = await sourceContainer.generateSasUrl({
permissions: ContainerSASPermissions.parse("rl"),
expiresOn: new Date(Date.now() + 24 * 60 * 60 * 1000),
});
const targetSas = await targetContainer.generateSasUrl({
permissions: ContainerSASPermissions.parse("rwl"),
expiresOn: new Date(Date.now() + 24 * 60 * 60 * 1000),
});
// Start batch translation
const response = await client.path("/document/batches").post({
body: {
inputs: [
{
source: { sourceUrl: sourceSas },
targets: [
{ targetUrl: targetSas, : },
],
},
],
},
});
operationId = (response.[])
..().();
import { isUnexpected, paginate } from "@azure-rest/ai-translation-document";
const statusResponse = await client.path("/document/batches/{id}", operationId).get();
if (!isUnexpected(statusResponse)) {
const status = statusResponse.body;
console.log(`Status: ${status.status}`);
console.log(`Total: ${status.summary.total}`);
console.log(`Success: ${status.summary.success}`);
}
// List documents with pagination
const docsResponse = await client.path("/document/batches/{id}/documents", operationId).get();
const documents = paginate(client, docsResponse);
for await (const doc of documents) {
console.log(`${doc.id}: ${doc.status}`);
}
const response = await client.path("/document/formats").get();
if (!isUnexpected(response)) {
for (const format of response.body.value) {
console.log(`${format.format}: ${format.fileExtensions.join(", ")}`);
}
}
// Text Translation
import type {
TranslatorCredential,
TranslatorTokenCredential,
} from "@azure-rest/ai-translation-text";
// Document Translation
import type {
DocumentTranslateParameters,
StartTranslationDetails,
TranslationStatus,
} from "@azure-rest/ai-translation-document";
language parameter to auto-detectisUnexpected(response) before accessing bodyThis skill is applicable to execute the workflow or actions described in the overview.