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telnyx-ai-inference-javascript

Access Telnyx LLM inference APIs, embeddings, and AI analytics for call insights and summaries. This skill provides JavaScript SDK examples.

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价格未确认★ 212 GitHub Stars目录更新于 · 2026年10月9日agent-skill

概览

Access Telnyx LLM inference APIs, embeddings, and AI analytics for call insights and summaries. This skill provides JavaScript SDK examples.

展开完整说明

以下为来源文档，不是本网站的操作指令。执行命令前请先核实权限。

Telnyx Ai Inference - JavaScript

Installation

npm install telnyx@6.74.2

Setup

import Telnyx from 'telnyx';

const client = new Telnyx({
  apiKey: process.env['TELNYX_API_KEY'], // This is the default and can be omitted
});

All examples below assume client is already initialized as shown above.

Error Handling

All API calls can fail with network errors, rate limits (429), validation errors (422), or authentication errors (401). Always handle errors in production code:

try {
  const result = await client.messages.send({ to: '+13125550001', from: '+13125550002', text: 'Hello' });
} catch (err) {
  if (err instanceof Telnyx.APIConnectionError) {
    console.error('Network error — check connectivity and retry');
  } else if (err instanceof Telnyx.RateLimitError) {
    // 429: rate limited — wait and retry with exponential backoff
    const retryAfter = err.headers?.['retry-after'] || 1;
    await new Promise(r => setTimeout(r, retryAfter * 1000));
  } else if (err instanceof Telnyx.APIError) {
    console.error(`API error ${err.status}: ${err.message}`);
    if (err.status === 422) {
      console.error('Validation error — check required fields and formats');
    }
  }
}

Common error codes: 401 invalid API key, 403 insufficient permissions, 404 resource not found, 422 validation error (check field formats), 429 rate limited (retry with exponential backoff).

Important Notes

Pagination: List methods return an auto-paginating iterator. Use for await (const item of result) { ... } to iterate through all pages automatically.

Transcribe speech to text

Transcribe speech to text. This endpoint is consistent with the OpenAI Transcription API and may be used with the OpenAI JS or Python SDK.

POST /ai/audio/transcriptions

import fs from 'fs';

const response = await client.ai.audio.transcribe({ model: 'distil-whisper/distil-large-v2' });

console.log(response.text);

Returns: duration (number), segments (array[object]), text (string), words (array[object])

Create a chat completion

Deprecated: Use POST /v2/ai/openai/chat/completions instead. Chat with a language model. This endpoint is consistent with the OpenAI Chat Completions API and may be used with the OpenAI JS or Python SDK.

POST /ai/chat/completions — Required: messages

Optional: api_key_ref (string), best_of (integer), early_stopping (boolean), enable_thinking (boolean), frequency_penalty (number), guided_choice (array[string]), guided_json (object), guided_regex (string), length_penalty (number), logprobs (boolean), max_tokens (integer), min_p (number), model (string), n (number), presence_penalty (number), response_format (object), seed (integer), stop (object), stream (boolean), temperature (number), tool_choice (enum: none, auto, required), tools (array[object]), top_logprobs (integer), top_p (number), use_beam_search (boolean)

const response = await client.ai.chat.createCompletion({
  messages: [
    { role: 'system', content: 'You are a friendly chatbot.' },
    { role: 'user', content: 'Hello, world!' },
  ],
});

console.log(response);

List conversations

Retrieve a list of all AI conversations configured by the user. Supports PostgREST-style query parameters for filtering. Examples are included for the standard metadata fields, but you can filter on any field in the metadata JSON object.

GET /ai/conversations

const conversations = await client.ai.conversations.list();

console.log(conversations.data);

Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)

Create a conversation

Create a new AI Conversation.

POST /ai/conversations

Optional: metadata (object), name (string)

const conversation = await client.ai.conversations.create();

console.log(conversation.id);

Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)

Aggregate Conversation Insights

Aggregate conversation insights by specified fields

GET /ai/conversations/conversation-insights/aggregates

const response = await client.ai.conversations.conversationInsights.aggregate();

console.log(response.data);

Returns: record_count (integer)

Get Insight Template Groups

Get all insight groups

GET /ai/conversations/insight-groups

// Automatically fetches more pages as needed.
for await (const insightTemplateGroup of client.ai.conversations.insightGroups.retrieveInsightGroups()) {
  console.log(insightTemplateGroup.id);
}

Returns: created_at (date-time), description (string), id (uuid), insights (array[object]), name (string), webhook (string)

Create Insight Template Group

Create a new insight group

POST /ai/conversations/insight-groups — Required: name

Optional: description (string), webhook (string)

const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.insightGroups({
  name: 'my-resource',
});

console.log(insightTemplateGroupDetail.data);

Returns: created_at (date-time), description (string), id (uuid), insights (array[object]), name (string), webhook (string)

Get Insight Template Group

Get insight group by ID

GET /ai/conversations/insight-groups/{group_id}

const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.retrieve(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateGroupDetail.data);

Returns: created_at (date-time), description (string), id (uuid), insights (array[object]), name (string), webhook (string)

Update Insight Template Group

Update an insight template group

PUT /ai/conversations/insight-groups/{group_id}

Optional: description (string), name (string), webhook (string)

const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.update(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateGroupDetail.data);

Returns: created_at (date-time), description (string), id (uuid), insights (array[object]), name (string), webhook (string)

Delete Insight Template Group

Delete insight group by ID

DELETE /ai/conversations/insight-groups/{group_id}

await client.ai.conversations.insightGroups.delete('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e');

Assign Insight Template To Group

Assign an insight to a group

POST /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/assign

await client.ai.conversations.insightGroups.insights.assign(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
  { group_id: '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e' },
);

Unassign Insight Template From Group

Remove an insight from a group

DELETE /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/unassign

await client.ai.conversations.insightGroups.insights.deleteUnassign(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
  { group_id: '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e' },
);

Get Insight Templates

Get all insights

GET /ai/conversations/insights

// Automatically fetches more pages as needed.
for await (const insightTemplate of client.ai.conversations.insights.list()) {
  console.log(insightTemplate.id);
}

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Create Insight Template

Create a new insight

POST /ai/conversations/insights — Required: instructions, name

Optional: json_schema (object), webhook (string)

const insightTemplateDetail = await client.ai.conversations.insights.create({
  instructions: 'You are a helpful assistant.',
  name: 'my-resource',
});

console.log(insightTemplateDetail.data);

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Get Insight Template

Get insight by ID

GET /ai/conversations/insights/{insight_id}

const insightTemplateDetail = await client.ai.conversations.insights.retrieve(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateDetail.data);

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Update Insight Template

Update an insight template

PUT /ai/conversations/insights/{insight_id}

Optional: instructions (string), json_schema (object), name (string), webhook (string)

const insightTemplateDetail = await client.ai.conversations.insights.update(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateDetail.data);

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Delete Insight Template

Delete insight by ID

DELETE /ai/conversations/insights/{insight_id}

await client.ai.conversations.insights.delete('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e');

Get a conversation

Retrieve a specific AI conversation by its ID.

GET /ai/conversations/{conversation_id}

const conversation = await client.ai.conversations.retrieve('550e8400-e29b-41d4-a716-446655440000');

console.log(conversation.data);

Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)

Update conversation metadata

Update metadata for a specific conversation.

PUT /ai/conversations/{conversation_id}

Optional: metadata (object)

const conversation = await client.ai.conversations.update('550e8400-e29b-41d4-a716-446655440000');

console.log(conversation.data);

Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)

Delete a conversation

Delete a specific conversation by its ID.

DELETE /ai/conversations/{conversation_id}

await client.ai.conversations.delete('550e8400-e29b-41d4-a716-446655440000');

Get insights for a conversation

Retrieve insights for a specific conversation

GET /ai/conversations/{conversation_id}/conversations-insights

const response = await client.ai.conversations.retrieveConversationsInsights('550e8400-e29b-41d4-a716-446655440000');

console.log(response.data);

Returns: conversation_insights (array[object]), created_at (date-time), id (string), status (enum: pending, in_progress, completed, failed)

Create Message

Add a new message to the conversation. Used to insert a new messages to a conversation manually ( without using chat endpoint )

POST /ai/conversations/{conversation_id}/message — Required: role

Optional: content (string), metadata (object), name (string), sent_at (date-time), tool_call_id (string), tool_calls (array[object]), tool_choice (object)

await client.ai.conversations.addMessage('182bd5e5-6e1a-4fe

查看来源 ↗

文件元数据

name: telnyx-ai-inference-javascript
description: >-
  Access Telnyx LLM inference APIs, embeddings, and AI analytics for call
  insights and summaries. This skill provides JavaScript SDK examples.
metadata:
  author: telnyx
  product: ai-inference
  language: javascript
  generated_by: telnyx-openapi-pipeline

查看原始文本

---
name: telnyx-ai-inference-javascript
description: >-
  Access Telnyx LLM inference APIs, embeddings, and AI analytics for call
  insights and summaries. This skill provides JavaScript SDK examples.
metadata:
  author: telnyx
  product: ai-inference
  language: javascript
  generated_by: telnyx-openapi-pipeline
---

<!-- Auto-generated from Telnyx OpenAPI specs. Do not edit. -->

# Telnyx Ai Inference - JavaScript

## Installation

```bash
npm install telnyx@6.74.2
```

## Setup

```javascript
import Telnyx from 'telnyx';

const client = new Telnyx({
  apiKey: process.env['TELNYX_API_KEY'], // This is the default and can be omitted
});
```

All examples below assume `client` is already initialized as shown above.

## Error Handling

All API calls can fail with network errors, rate limits (429), validation errors (422),
or authentication errors (401). Always handle errors in production code:

```javascript
try {
  const result = await client.messages.send({ to: '+13125550001', from: '+13125550002', text: 'Hello' });
} catch (err) {
  if (err instanceof Telnyx.APIConnectionError) {
    console.error('Network error — check connectivity and retry');
  } else if (err instanceof Telnyx.RateLimitError) {
    // 429: rate limited — wait and retry with exponential backoff
    const retryAfter = err.headers?.['retry-after'] || 1;
    await new Promise(r => setTimeout(r, retryAfter * 1000));
  } else if (err instanceof Telnyx.APIError) {
    console.error(`API error ${err.status}: ${err.message}`);
    if (err.status === 422) {
      console.error('Validation error — check required fields and formats');
    }
  }
}
```

Common error codes: `401` invalid API key, `403` insufficient permissions,
`404` resource not found, `422` validation error (check field formats),
`429` rate limited (retry with exponential backoff).

## Important Notes

- **Pagination:** List methods return an auto-paginating iterator. Use `for await (const item of result) { ... }` to iterate through all pages automatically.

## Transcribe speech to text

Transcribe speech to text. This endpoint is consistent with the [OpenAI Transcription API](https://platform.openai.com/docs/api-reference/audio/createTranscription) and may be used with the OpenAI JS or Python SDK.

`POST /ai/audio/transcriptions`

```javascript
import fs from 'fs';

const response = await client.ai.audio.transcribe({ model: 'distil-whisper/distil-large-v2' });

console.log(response.text);
```

Returns: `duration` (number), `segments` (array[object]), `text` (string), `words` (array[object])

## Create a chat completion

**Deprecated**: Use `POST /v2/ai/openai/chat/completions` instead. Chat with a language model. This endpoint is consistent with the [OpenAI Chat Completions API](https://platform.openai.com/docs/api-reference/chat) and may be used with the OpenAI JS or Python SDK.

`POST /ai/chat/completions` — Required: `messages`

Optional: `api_key_ref` (string), `best_of` (integer), `early_stopping` (boolean), `enable_thinking` (boolean), `frequency_penalty` (number), `guided_choice` (array[string]), `guided_json` (object), `guided_regex` (string), `length_penalty` (number), `logprobs` (boolean), `max_tokens` (integer), `min_p` (number), `model` (string), `n` (number), `presence_penalty` (number), `response_format` (object), `seed` (integer), `stop` (object), `stream` (boolean), `temperature` (number), `tool_choice` (enum: none, auto, required), `tools` (array[object]), `top_logprobs` (integer), `top_p` (number), `use_beam_search` (boolean)

```javascript
const response = await client.ai.chat.createCompletion({
  messages: [
    { role: 'system', content: 'You are a friendly chatbot.' },
    { role: 'user', content: 'Hello, world!' },
  ],
});

console.log(response);
```

## List conversations

Retrieve a list of all AI conversations configured by the user. Supports [PostgREST-style query parameters](https://postgrest.org/en/stable/api.html#horizontal-filtering-rows) for filtering. Examples are included for the standard metadata fields, but you can filter on any field in the metadata JSON object.

`GET /ai/conversations`

```javascript
const conversations = await client.ai.conversations.list();

console.log(conversations.data);
```

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

## Create a conversation

Create a new AI Conversation.

`POST /ai/conversations`

Optional: `metadata` (object), `name` (string)

```javascript
const conversation = await client.ai.conversations.create();

console.log(conversation.id);
```

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

## Aggregate Conversation Insights

Aggregate conversation insights by specified fields

`GET /ai/conversations/conversation-insights/aggregates`

```javascript
const response = await client.ai.conversations.conversationInsights.aggregate();

console.log(response.data);
```

Returns: `record_count` (integer)

## Get Insight Template Groups

Get all insight groups

`GET /ai/conversations/insight-groups`

```javascript
// Automatically fetches more pages as needed.
for await (const insightTemplateGroup of client.ai.conversations.insightGroups.retrieveInsightGroups()) {
  console.log(insightTemplateGroup.id);
}
```

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

## Create Insight Template Group

Create a new insight group

`POST /ai/conversations/insight-groups` — Required: `name`

Optional: `description` (string), `webhook` (string)

```javascript
const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.insightGroups({
  name: 'my-resource',
});

console.log(insightTemplateGroupDetail.data);
```

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

## Get Insight Template Group

Get insight group by ID

`GET /ai/conversations/insight-groups/{group_id}`

```javascript
const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.retrieve(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateGroupDetail.data);
```

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

## Update Insight Template Group

Update an insight template group

`PUT /ai/conversations/insight-groups/{group_id}`

Optional: `description` (string), `name` (string), `webhook` (string)

```javascript
const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.update(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateGroupDetail.data);
```

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

## Delete Insight Template Group

Delete insight group by ID

`DELETE /ai/conversations/insight-groups/{group_id}`

```javascript
await client.ai.conversations.insightGroups.delete('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e');
```

## Assign Insight Template To Group

Assign an insight to a group

`POST /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/assign`

```javascript
await client.ai.conversations.insightGroups.insights.assign(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
  { group_id: '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e' },
);
```

## Unassign Insight Template From Group

Remove an insight from a group

`DELETE /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/unassign`

```javascript
await client.ai.conversations.insightGroups.insights.deleteUnassign(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
  { group_id: '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e' },
);
```

## Get Insight Templates

Get all insights

`GET /ai/conversations/insights`

```javascript
// Automatically fetches more pages as needed.
for await (const insightTemplate of client.ai.conversations.insights.list()) {
  console.log(insightTemplate.id);
}
```

Returns: `created_at` (date-time), `id` (uuid), `insight_type` (enum: custom, default), `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

## Create Insight Template

Create a new insight

`POST /ai/conversations/insights` — Required: `instructions`, `name`

Optional: `json_schema` (object), `webhook` (string)

```javascript
const insightTemplateDetail = await client.ai.conversations.insights.create({
  instructions: 'You are a helpful assistant.',
  name: 'my-resource',
});

console.log(insightTemplateDetail.data);
```

Returns: `created_at` (date-time), `id` (uuid), `insight_type` (enum: custom, default), `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

## Get Insight Template

Get insight by ID

`GET /ai/conversations/insights/{insight_id}`

```javascript
const insightTemplateDetail = await client.ai.conversations.insights.retrieve(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateDetail.data);
```

Returns: `created_at` (date-time), `id` (uuid), `insight_type` (enum: custom, default), `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

## Update Insight Template

Update an insight template

`PUT /ai/conversations/insights/{insight_id}`

Optional: `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

```javascript
const insightTemplateDetail = await client.ai.conversations.insights.update(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateDetail.data);
```

Returns: `created_at` (date-time), `id` (uuid), `insight_type` (enum: custom, default), `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

## Delete Insight Template

Delete insight by ID

`DELETE /ai/conversations/insights/{insight_id}`

```javascript
await client.ai.conversations.insights.delete('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e');
```

## Get a conversation

Retrieve a specific AI conversation by its ID.

`GET /ai/conversations/{conversation_id}`

```javascript
const conversation = await client.ai.conversations.retrieve('550e8400-e29b-41d4-a716-446655440000');

console.log(conversation.data);
```

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

## Update conversation metadata

Update metadata for a specific conversation.

`PUT /ai/conversations/{conversation_id}`

Optional: `metadata` (object)

```javascript
const conversation = await client.ai.conversations.update('550e8400-e29b-41d4-a716-446655440000');

console.log(conversation.data);
```

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

## Delete a conversation

Delete a specific conversation by its ID.

`DELETE /ai/conversations/{conversation_id}`

```javascript
await client.ai.conversations.delete('550e8400-e29b-41d4-a716-446655440000');
```

## Get insights for a conversation

Retrieve insights for a specific conversation

`GET /ai/conversations/{conversation_id}/conversations-insights`

```javascript
const response = await client.ai.conversations.retrieveConversationsInsights('550e8400-e29b-41d4-a716-446655440000');

console.log(response.data);
```

Returns: `conversation_insights` (array[object]), `created_at` (date-time), `id` (string), `status` (enum: pending, in_progress, completed, failed)

## Create Message

Add a new message to the conversation. Used to insert a new messages to a conversation manually ( without using chat endpoint )

`POST /ai/conversations/{conversation_id}/message` — Required: `role`

Optional: `content` (string), `metadata` (object), `name` (string), `sent_at` (date-time), `tool_call_id` (string), `tool_calls` (array[object]), `tool_choice` (object)

```javascript
await client.ai.conversations.addMessage('182bd5e5-6e1a-4fe

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许可证: MIT

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The skill is auto-generated and may not cover all Telnyx AI endpoints or edge cases, but it provides a solid foundation.
Quality score needs review
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Stars/forks activity: 212 stars, 22 forks; issue activity unavailable in current metadata
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2先让 Agent 提出计划，批准环境配置和费用，再进行隔离的小规模测试。
3检查输出和变更文件，只报告实际执行结果，并保留来源版本以便复现。

请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。

来源与使用须知

已收录

仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。

来源仓库: team-telnyx/ai
许可证: MIT
版本: 1.0.0
最近 GitHub 推送: 2026年9月5日
目录更新于: 2026年10月9日
技能指令路径: providers/claude/plugins/telnyx-ai/skills/telnyx-ai-inference-javascript/SKILL.md @ 0443b296fd5b

版本来自目录元数据，使用前请核实来源发布记录。

质量

67/100

有潜力

信任

56/100

Do not auto-install

审计

72/100

需审查

打开完整审计查看评估报告

Dependency or permission surface needs review
Permission surface may require sandboxing
The SKILL.md metadata description appears truncated in the parsed output (shows '>-' instead of the full description), though the actual file contains the full description.
The skill is auto-generated and may not cover all Telnyx AI endpoints or edge cases, but it provides a solid foundation.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 212 stars, 22 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
结果: —

复制不等于安装。安装数需有成功安装回报，不代表全面的质量保证。

Agent 接入

本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号，让 Agent 无需抓取界面即可排序。

打开安装 API LLM 文本格式打开 Manifest 自动解析计划

更多详情

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      "documentation": "Strong README/SKILL.md context",
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    "label": "Needs first agent run",
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    "warnings": [
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      "Permission surface may require sandboxing",
      "The SKILL.md metadata description appears truncated in the parsed output (shows '>-' instead of the full description), though the actual file contains the full description.",
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      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Stars/forks activity: 212 stars, 22 forks; issue activity unavailable in current metadata",
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    "The SKILL.md metadata description appears truncated in the parsed output (shows '>-' instead of the full description), though the actual file contains the full description.",
    "No OpenAgentSkill engagement data yet",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "The skill is auto-generated and may not cover all Telnyx AI endpoints or edge cases, but it provides a solid foundation."
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      "Audit: 72/100 Needs review",
      "Safety: 32/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
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此列表来自公开来源，维护者认领获批前不会标记为官方。

创作者: team-telnyx
来源: team-telnyx/ai
收录方: OpenAgentSkill 社区索引

归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。

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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/team-telnyx-telnyx-ai-inference-javascript?metric=listed&label=Listed)](https://www.openagentskill.com/skills/team-telnyx-telnyx-ai-inference-javascript?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
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概览

Telnyx Ai Inference - JavaScript

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