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telnyx-ai-inference-ruby

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

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Resumen

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

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Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

Telnyx Ai Inference - Ruby

Installation

gem install telnyx

Setup

require "telnyx"

client = Telnyx::Client.new(
  api_key: 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:

begin
  result = client.messages.send_(to: "+13125550001", from: "+13125550002", text: "Hello")
rescue Telnyx::Errors::APIConnectionError
  puts "Network error — check connectivity and retry"
rescue Telnyx::Errors::RateLimitError
  # 429: rate limited — wait and retry with exponential backoff
  sleep(1) # Check Retry-After header for actual delay
rescue Telnyx::Errors::APIStatusError => e
  puts "API error #{e.status}: #{e.message}"
  if e.status == 422
    puts "Validation error — check required fields and formats"
  end
end

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: Use .auto_paging_each for automatic iteration: page.auto_paging_each { |item| puts item.id }.

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

response = client.ai.audio.transcribe(model: :"distil-whisper/distil-large-v2")

puts(response)

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)

response = client.ai.chat.create_completion(
  messages: [{content: "You are a friendly chatbot.", role: :system}, {content: "Hello, world!", role: :user}]
)

puts(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

conversations = client.ai.conversations.list

puts(conversations)

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)

conversation = client.ai.conversations.create

puts(conversation)

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

response = client.ai.conversations.conversation_insights.aggregate

puts(response)

Returns: record_count (integer)

Get Insight Template Groups

Get all insight groups

GET /ai/conversations/insight-groups

page = client.ai.conversations.insight_groups.retrieve_insight_groups

puts(page)

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)

insight_template_group_detail = client.ai.conversations.insight_groups.insight_groups(name: "my-resource")

puts(insight_template_group_detail)

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}

insight_template_group_detail = client.ai.conversations.insight_groups.retrieve("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_group_detail)

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)

insight_template_group_detail = client.ai.conversations.insight_groups.update("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_group_detail)

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}

result = client.ai.conversations.insight_groups.delete("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(result)

Assign Insight Template To Group

Assign an insight to a group

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

result = client.ai.conversations.insight_groups.insights.assign(
  "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
  group_id: "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e"
)

puts(result)

Unassign Insight Template From Group

Remove an insight from a group

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

result = client.ai.conversations.insight_groups.insights.delete_unassign(
  "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
  group_id: "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e"
)

puts(result)

Get Insight Templates

Get all insights

GET /ai/conversations/insights

page = client.ai.conversations.insights.list

puts(page)

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)

insight_template_detail = client.ai.conversations.insights.create(instructions: "You are a helpful assistant.", name: "my-resource")

puts(insight_template_detail)

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}

insight_template_detail = client.ai.conversations.insights.retrieve("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_detail)

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)

insight_template_detail = client.ai.conversations.insights.update("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_detail)

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}

result = client.ai.conversations.insights.delete("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(result)

Get a conversation

Retrieve a specific AI conversation by its ID.

GET /ai/conversations/{conversation_id}

conversation = client.ai.conversations.retrieve("550e8400-e29b-41d4-a716-446655440000")

puts(conversation)

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)

conversation = client.ai.conversations.update("550e8400-e29b-41d4-a716-446655440000")

puts(conversation)

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}

result = client.ai.conversations.delete("550e8400-e29b-41d4-a716-446655440000")

puts(result)

Get insights for a conversation

Retrieve insights for a specific conversation

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

response = client.ai.conversations.retrieve_conversations_insights("550e8400-e29b-41d4-a716-446655440000")

puts(response)

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)

result = client.ai.conversations.add_message("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", role: "user")

puts(result)

Get conversation messages

Retrieve messages for a specific conversation, including tool calls made by the assistant.

GET /ai/conversations/{conversation_id}/messages

page = client.ai.conversations.messages.list("550e8400-e29b-41d4-a716-446655440000")

puts(page)

Returns: created_at (date-time), role (enum: user, assistant, tool), sent_at (date-time), text (string), tool_calls (array[object])

Get Tasks by Status

Retrieve tasks for the user that are either queued, processing, failed, success or partial_success based on the query string. Defaults to queued and processing.

GET /ai/embeddings

embeddings = client.ai.embeddings.list

puts(embeddings)

Returns: bucket (string), created_at (date-time), finished_at (date-time), status (enum: queued, processing, success, failure, partial_success), task_id (string), task_name (string),

Metadatos del archivo
name: telnyx-ai-inference-ruby
description: >-
  Access Telnyx LLM inference APIs, embeddings, and AI analytics for call
  insights and summaries. This skill provides Ruby SDK examples.
metadata:
  author: telnyx
  product: ai-inference
  language: ruby
  generated_by: telnyx-openapi-pipeline
Ver texto original
---
name: telnyx-ai-inference-ruby
description: >-
  Access Telnyx LLM inference APIs, embeddings, and AI analytics for call
  insights and summaries. This skill provides Ruby SDK examples.
metadata:
  author: telnyx
  product: ai-inference
  language: ruby
  generated_by: telnyx-openapi-pipeline
---

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

# Telnyx Ai Inference - Ruby

## Installation

```bash
gem install telnyx
```

## Setup

```ruby
require "telnyx"

client = Telnyx::Client.new(
  api_key: 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:

```ruby
begin
  result = client.messages.send_(to: "+13125550001", from: "+13125550002", text: "Hello")
rescue Telnyx::Errors::APIConnectionError
  puts "Network error — check connectivity and retry"
rescue Telnyx::Errors::RateLimitError
  # 429: rate limited — wait and retry with exponential backoff
  sleep(1) # Check Retry-After header for actual delay
rescue Telnyx::Errors::APIStatusError => e
  puts "API error #{e.status}: #{e.message}"
  if e.status == 422
    puts "Validation error — check required fields and formats"
  end
end
```

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:** Use `.auto_paging_each` for automatic iteration: `page.auto_paging_each { |item| puts item.id }`.

## 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`

```ruby
response = client.ai.audio.transcribe(model: :"distil-whisper/distil-large-v2")

puts(response)
```

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)

```ruby
response = client.ai.chat.create_completion(
  messages: [{content: "You are a friendly chatbot.", role: :system}, {content: "Hello, world!", role: :user}]
)

puts(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`

```ruby
conversations = client.ai.conversations.list

puts(conversations)
```

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)

```ruby
conversation = client.ai.conversations.create

puts(conversation)
```

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`

```ruby
response = client.ai.conversations.conversation_insights.aggregate

puts(response)
```

Returns: `record_count` (integer)

## Get Insight Template Groups

Get all insight groups

`GET /ai/conversations/insight-groups`

```ruby
page = client.ai.conversations.insight_groups.retrieve_insight_groups

puts(page)
```

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)

```ruby
insight_template_group_detail = client.ai.conversations.insight_groups.insight_groups(name: "my-resource")

puts(insight_template_group_detail)
```

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}`

```ruby
insight_template_group_detail = client.ai.conversations.insight_groups.retrieve("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_group_detail)
```

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)

```ruby
insight_template_group_detail = client.ai.conversations.insight_groups.update("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_group_detail)
```

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}`

```ruby
result = client.ai.conversations.insight_groups.delete("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(result)
```

## Assign Insight Template To Group

Assign an insight to a group

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

```ruby
result = client.ai.conversations.insight_groups.insights.assign(
  "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
  group_id: "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e"
)

puts(result)
```

## Unassign Insight Template From Group

Remove an insight from a group

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

```ruby
result = client.ai.conversations.insight_groups.insights.delete_unassign(
  "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
  group_id: "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e"
)

puts(result)
```

## Get Insight Templates

Get all insights

`GET /ai/conversations/insights`

```ruby
page = client.ai.conversations.insights.list

puts(page)
```

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)

```ruby
insight_template_detail = client.ai.conversations.insights.create(instructions: "You are a helpful assistant.", name: "my-resource")

puts(insight_template_detail)
```

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}`

```ruby
insight_template_detail = client.ai.conversations.insights.retrieve("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_detail)
```

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)

```ruby
insight_template_detail = client.ai.conversations.insights.update("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_detail)
```

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}`

```ruby
result = client.ai.conversations.insights.delete("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(result)
```

## Get a conversation

Retrieve a specific AI conversation by its ID.

`GET /ai/conversations/{conversation_id}`

```ruby
conversation = client.ai.conversations.retrieve("550e8400-e29b-41d4-a716-446655440000")

puts(conversation)
```

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)

```ruby
conversation = client.ai.conversations.update("550e8400-e29b-41d4-a716-446655440000")

puts(conversation)
```

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}`

```ruby
result = client.ai.conversations.delete("550e8400-e29b-41d4-a716-446655440000")

puts(result)
```

## Get insights for a conversation

Retrieve insights for a specific conversation

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

```ruby
response = client.ai.conversations.retrieve_conversations_insights("550e8400-e29b-41d4-a716-446655440000")

puts(response)
```

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)

```ruby
result = client.ai.conversations.add_message("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", role: "user")

puts(result)
```

## Get conversation messages

Retrieve messages for a specific conversation, including tool calls made by the assistant.

`GET /ai/conversations/{conversation_id}/messages`

```ruby
page = client.ai.conversations.messages.list("550e8400-e29b-41d4-a716-446655440000")

puts(page)
```

Returns: `created_at` (date-time), `role` (enum: user, assistant, tool), `sent_at` (date-time), `text` (string), `tool_calls` (array[object])

## Get Tasks by Status

Retrieve tasks for the user that are either `queued`, `processing`, `failed`, `success` or `partial_success` based on the query string. Defaults to `queued` and `processing`.

`GET /ai/embeddings`

```ruby
embeddings = client.ai.embeddings.list

puts(embeddings)
```

Returns: `bucket` (string), `created_at` (date-time), `finished_at` (date-time), `status` (enum: queued, processing, success, failure, partial_success), `task_id` (string), `task_name` (string),

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  • The excerpt is truncated; ensure the full document covers all endpoints and parameters consistently.
  • 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
Abrir auditoría completa

Las herramientas son indicios de metadatos, no compatibilidad probada. Los prompts son sugerencias.

Empieza con una tarea pequeña

  1. 1Lee la fuente y confirma entradas, resultados, dependencias y permisos.
  2. 2Pide un plan al agente. Aprueba la configuración y los costes antes de probar en un entorno aislado.
  3. 3Comprueba resultados y archivos modificados. Informa solo de lo ejecutado y conserva la revisión de la fuente.

Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.

Fuente y notas de uso

Indexado

Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.

Repositorio fuente
team-telnyx/ai
Licencia
MIT
Versión
1.0.0
Último push de GitHub
5 sept 2026
Registro actualizado
9 oct 2026

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

67/100

Prometedor

Confianza

57/100

Do not auto-install

Auditoría

73/100

Requiere revisión

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • SKILL.md is auto-generated and may lack explicit safety guidance beyond standard error handling.
  • The excerpt is truncated; ensure the full document covers all endpoints and parameters consistently.
  • 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
—
Resultados
—

Copiar no es instalar. Los recuentos requieren un informe de instalación correcta, no garantizan calidad general.

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La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.

Más detalles
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