>- Access Telnyx LLM inference APIs, embeddings, and AI analytics for call insights and summaries. This skill provides REST API (curl) examples.
npx skills add https://github.com/team-telnyx/ai --skill telnyx-ai-inference-curl
<!-- Auto-generated from Telnyx OpenAPI specs. Do not edit. -->
# curl is pre-installed on macOS, Linux, and Windows 10+
export TELNYX_API_KEY="YOUR_API_KEY_HERE"
All examples below use $TELNYX_API_KEY for authentication.
All API calls can fail with network errors, rate limits (429), validation errors (422),
or authentication errors (401). Always handle errors in production code:
# Check HTTP status code in response
response=$(curl -s -w "\n%{http_code}" \
-X POST "https://api.telnyx.com/v2/messages" \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{"to": "+13125550001", "from": "+13125550002", "text": "Hello"}')
http_code=$(echo "$response" | tail -1)
body=$(echo "$response" | sed '$d')
case $http_code in
2*) echo "Success: $body" ;;
422) echo "Validation error — check required fields and formats" ;;
429) echo "Rate limited — retry after delay"; sleep 1 ;;
401) echo "Authentication failed — check TELNYX_API_KEY" ;;
*) echo "Error $http_code: $body" ;;
esac
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).
page[number] and page[size] query parameters to navigate pages. Check meta.total_pages in the response.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
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-F "file=@/path/to/file" \
-F "file_url=https://example.com/file.mp3" \
-F "model=distil-whisper/distil-large-v2" \
-F "response_format=json" \
-F "timestamp_granularities[]=segment" \
-F "language=en-US" \
-F "model_config={'smart_format': True, 'punctuate': True}" \
"https://api.telnyx.com/v2/ai/audio/transcriptions"
Returns: duration (number), segments (array[object]), text (string)
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), stream (boolean), temperature (number), tool_choice (enum: none, auto, required), tools (array[object]), top_logprobs (integer), top_p (number), use_beam_search (boolean)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"messages": [
{
"role": "system",
"content": "You are a friendly chatbot."
},
{
"role": "user",
"content": "Hello, world!"
}
]
}' \
"https://api.telnyx.com/v2/ai/chat/completions"
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
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/conversations"
Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)
Create a new AI Conversation.
POST /ai/conversations
Optional: metadata (object), name (string)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
"https://api.telnyx.com/v2/ai/conversations"
Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)
Get all insight groups
GET /ai/conversations/insight-groups
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/conversations/insight-groups"
Returns: created_at (date-time), description (string), id (uuid), insights (array[object]), name (string), webhook (string)
Create a new insight group
POST /ai/conversations/insight-groups — Required: name
Optional: description (string), webhook (string)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "my-resource"
}' \
"https://api.telnyx.com/v2/ai/conversations/insight-groups"
Returns: created_at (date-time), description (string), id (uuid), insights (array[object]), name (string), webhook (string)
Get insight group by ID
GET /ai/conversations/insight-groups/{group_id}
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/conversations/insight-groups/{group_id}"
Returns: created_at (date-time), description (string), id (uuid), insights (array[object]), name (string), webhook (string)
Update an insight template group
PUT /ai/conversations/insight-groups/{group_id}
Optional: description (string), name (string), webhook (string)
curl \
-X PUT \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
"https://api.telnyx.com/v2/ai/conversations/insight-groups/{group_id}"
Returns: created_at (date-time), description (string), id (uuid), insights (array[object]), name (string), webhook (string)
Delete insight group by ID
DELETE /ai/conversations/insight-groups/{group_id}
curl \
-X DELETE \
-H "Authorization: Bearer $TELNYX_API_KEY" \
"https://api.telnyx.com/v2/ai/conversations/insight-groups/{group_id}"
Assign an insight to a group
POST /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/assign
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
"https://api.telnyx.com/v2/ai/conversations/insight-groups/{group_id}/insights/{insight_id}/assign"
Remove an insight from a group
DELETE /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/unassign
curl \
-X DELETE \
-H "Authorization: Bearer $TELNYX_API_KEY" \
"https://api.telnyx.com/v2/ai/conversations/insight-groups/{group_id}/insights/{insight_id}/unassign"
Get all insights
GET /ai/conversations/insights
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/conversations/insights"
Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)
Create a new insight
POST /ai/conversations/insights — Required: instructions, name
Optional: json_schema (object), webhook (string)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"instructions": "You are a helpful assistant.",
"name": "my-resource"
}' \
"https://api.telnyx.com/v2/ai/conversations/insights"
Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)
Get insight by ID
GET /ai/conversations/insights/{insight_id}
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/conversations/insights/{insight_id}"
Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)
Update an insight template
PUT /ai/conversations/insights/{insight_id}
Optional: instructions (string), json_schema (object), name (string), webhook (string)
curl \
-X PUT \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
"https://api.telnyx.com/v2/ai/conversations/insights/{insight_id}"
Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)
Delete insight by ID
DELETE /ai/conversations/insights/{insight_id}
curl \
-X DELETE \
-H "Authorization: Bearer $TELNYX_API_KEY" \
"https://api.telnyx.com/v2/ai/conversations/insights/{insight_id}"
Retrieve a specific AI conversation by its ID.
GET /ai/conversations/{conversation_id}
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/conversations/550e8400-e29b-41d4-a716-446655440000"
Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)
Update metadata for a specific conversation.
PUT /ai/conversations/{conversation_id}
Optional: metadata (object)
curl \
-X PUT \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
"https://api.telnyx.com/v2/ai/conversations/550e8400-e29b-41d4-a716-446655440000"
Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)
Delete a specific conversation by its ID.
DELETE /ai/conversations/{conversation_id}
curl \
-X DELETE \
-H "Authorization: Bearer $TELNYX_API_KEY" \
"https://api.telnyx.com/v2/ai/conversations/550e8400-e29b-41d4-a716-446655440000"
Retrieve insights for a specific conversation
GET /ai/conversations/{conversation_id}/conversations-insights
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/conversations/550e8400-e29b-41d4-a716-446655440000/conversations-insights"
Returns: conversation_insights (array[object]), created_at (date-time), id (string), status (enum: pending, in_progress, completed, failed)
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)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"role": "user"
}' \
"https://api.telnyx.com/v2/ai/conversations/550e8400-e29b-41d4-a716-446655440000/message"
Retrieve messages for a specific conversation, including tool calls made by the assistant.
GET /ai/conversations/{conversation_id}/messages
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/conversations/550e8400-e29b-41d4-a716-446655440000/messages"
Returns: created_at (date-time), role (enum: user, assistant, tool), sent_at (date-time), text (string), tool_calls (array[object])
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
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/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), user_id (string)
Perform embedding on a Telnyx Storage Bucket using an embedding model. The current supported file types are:
POST /ai/embeddings — Required: bucket_name
Optional: document_chunk_overlap_size (integer), document_chunk_size (integer), embedding_model (object), loader (object)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"bucket_name": "my-bucket"
}' \
"https://api.telnyx.com/v2/ai/embeddings"
Returns: created_at (string), finished_at (string | null), status (string), task_id (uuid), task_name (string), user_id (uuid)
Get all embedding buckets for a user.
GET /ai/embeddings/buckets
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/embeddings/buckets"
Returns: buckets (array[string])
Get all embedded files for a given user bucket, including their processing status.
GET /ai/embeddings/buckets/{bucket_name}
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/embeddings/buckets/{bucket_name}"
Returns: created_at (date-time), error_reason (string), filename (string), last_embedded_at (date-time), status (string), updated_at (date-time)
Deletes an entire bucket's embeddings and disables the bucket for AI-use, returning it to normal storage pricing.
DELETE /ai/embeddings/buckets/{bucket_name}
curl \
-X DELETE \
-H "Authorization: Bearer $TELNYX_API_KEY" \
"https://api.telnyx.com/v2/ai/embeddings/buckets/{bucket_name}"
Perform a similarity search on a Telnyx Storage Bucket, returning the most similar num_docs document chunks to the query. Currently the only available distance metric is cosine similarity which will return a distance between 0 and 1. The lower the distance, the more similar the returned document chunks are to the query.
POST /ai/embeddings/similarity-search — Required: bucket_name, query
Optional: num_of_docs (integer)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"bucket_name": "my-bucket",
"query": "What is Telnyx?"
}' \
"https://api.telnyx.com/v2/ai/embeddings/similarity-search"
Returns: distance (number), document_chunk (string), metadata (object)
Embed website content from a specified URL, including child pages up to 5 levels deep within the same domain. The process crawls and loads content from the main URL and its linked pages into a Telnyx Cloud Storage bucket.
POST /ai/embeddings/url — Required: url, bucket_name
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"url": "https://example.com/resource",
"bucket_name": "my-bucket"
}' \
"https://api.telnyx.com/v2/ai/embeddings/url"
Returns: created_at (string), finished_at (string | null), status (string), task_id (uuid), task_name (string), user_id (uuid)
Check the status of a current embedding task. Will be one of the following:
queued - Task is waiting to be picked up by a workerprocessing - The embedding task is runningsuccess - Task completed successfully and the bucket is embeddedfailure - Task failed and no files were embedded successfullypartial_success - Some files were embedded successfully, but at least one failedGET /ai/embeddings/{task_id}
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/embeddings/{task_id}"
Returns: created_at (string), finished_at (string), status (enum: queued, processing, success, failure, partial_success), task_id (uuid), task_name (string)
Retrieve a list of all fine tuning jobs created by the user.
GET /ai/fine_tuning/jobs
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/fine_tuning/jobs"
Returns: created_at (integer), finished_at (integer | null), hyperparameters (object), id (string), model (string), organization_id (string), status (enum: queued, running, succeeded, failed, cancelled), trained_tokens (integer | null), training_file (string)
Create a new fine tuning job.
POST /ai/fine_tuning/jobs — Required: model, training_file
Optional: hyperparameters (object), suffix (string)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-4o",
"training_file": "training-data.jsonl"
}' \
"https://api.telnyx.com/v2/ai/fine_tuning/jobs"
Returns: created_at (integer), finished_at (integer | null), hyperparameters (object), id (string), model (string), organization_id (string), status (enum: queued, running, succeeded, failed, cancelled), trained_tokens (integer | null), training_file (string)
Retrieve a fine tuning job by job_id.
GET /ai/fine_tuning/jobs/{job_id}
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/fine_tuning/jobs/{job_id}"
Returns: created_at (integer), finished_at (integer | null), hyperparameters (object), id (string), model (string), organization_id (string), status (enum: queued, running, succeeded, failed, cancelled), trained_tokens (integer | null), training_file (string)
Cancel a fine tuning job.
POST /ai/fine_tuning/jobs/{job_id}/cancel
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
"https://api.telnyx.com/v2/ai/fine_tuning/jobs/{job_id}/cancel"
Returns: created_at (integer), finished_at (integer | null), hyperparameters (object), id (string), model (string), organization_id (string), status (enum: queued, running, succeeded, failed, cancelled), trained_tokens (integer | null), training_file (string)
This endpoint returns a list of Open Source and OpenAI models that are available for use. Note: Model id's will be in the form {source}/{model_name}. For example openai/gpt-4 or mistralai/Mistral-7B-Instruct-v0.1 consistent with HuggingFace naming conventions.
GET /ai/models
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/models"
Returns: created (integer), id (string), object (string), owned_by (string)
Creates an embedding vector representing the input text. This endpoint is compatible with the OpenAI Embeddings API and may be used with the OpenAI JS or Python SDK by setting the base URL to https://api.telnyx.com/v2/ai/openai.
POST /ai/openai/embeddings — Required: input, model
Optional: dimensions (integer), encoding_format (enum: float, base64), user (string)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "The quick brown fox jumps over the lazy dog",
"model": "thenlper/gte-large"
}' \
"https://api.telnyx.com/v2/ai/openai/embeddings"
Returns: data (array[object]), model (string), object (string), usage (object)
Returns a list of available embedding models. This endpoint is compatible with the OpenAI Models API format.
GET /ai/openai/embeddings/models
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/ai/openai/embeddings/models"
Returns: created (integer), id (string), object (string), owned_by (string)
Generate a summary of a file's contents. Supports the following text formats:
Supports the following media formats (billed for both the transcription and summary):
POST /ai/summarize — Required: bucket, filename
Optional: system_prompt (string)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"bucket": "my-bucket",
"filename": "data.csv"
}' \
"https://api.telnyx.com/v2/ai/summarize"
Returns: summary (string)
Retrieves all Speech to Text batch report requests for the authenticated user
GET /legacy/reporting/batch_detail_records/speech_to_text
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/legacy/reporting/batch_detail_records/speech_to_text"
Returns: created_at (date-time), download_link (string), end_date (date-time), id (string), record_type (string), start_date (date-time), status (enum: PENDING, COMPLETE, FAILED, EXPIRED)
Creates a new Speech to Text batch report request with the specified filters
POST /legacy/reporting/batch_detail_records/speech_to_text — Required: start_date, end_date
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"start_date": "2020-07-01T00:00:00-06:00",
"end_date": "2020-07-01T00:00:00-06:00"
}' \
"https://api.telnyx.com/v2/legacy/reporting/batch_detail_records/speech_to_text"
Returns: created_at (date-time), download_link (string), end_date (date-time), id (string), record_type (string), start_date (date-time), status (enum: PENDING, COMPLETE, FAILED, EXPIRED)
Retrieves a specific Speech to Text batch report request by ID
GET /legacy/reporting/batch_detail_records/speech_to_text/{id}
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/legacy/reporting/batch_detail_records/speech_to_text/550e8400-e29b-41d4-a716-446655440000"
Returns: created_at (date-time), download_link (string), end_date (date-time), id (string), record_type (string), start_date (date-time), status (enum: PENDING, COMPLETE, FAILED, EXPIRED)
Deletes a specific Speech to Text batch report request by ID
DELETE /legacy/reporting/batch_detail_records/speech_to_text/{id}
curl \
-X DELETE \
-H "Authorization: Bearer $TELNYX_API_KEY" \
"https://api.telnyx.com/v2/legacy/reporting/batch_detail_records/speech_to_text/550e8400-e29b-41d4-a716-446655440000"
Returns: created_at (date-time), download_link (string), end_date (date-time), id (string), record_type (string), start_date (date-time), status (enum: PENDING, COMPLETE, FAILED, EXPIRED)
Generate and fetch speech to text usage report synchronously. This endpoint will both generate and fetch the speech to text report over a specified time period.
GET /legacy/reporting/usage_reports/speech_to_text
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/legacy/reporting/usage_reports/speech_to_text?start_date=2020-07-02T00:00:00-06:00&end_date=2020-07-01T00:00:00-06:00"
Returns: data (object)
Open a WebSocket connection to stream audio and receive transcriptions in real-time. Authentication is provided via the standard Authorization: Bearer header. Supported engines: Azure, Deepgram, Google, Telnyx.
GET /speech-to-text/transcription
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/speech-to-text/transcription?transcription_engine=Telnyx&input_format=mp3&language=en-US&interim_results=True&endpointing=500&redact=pci&keyterm=Telnyx&keywords=Telnyx,SIP,WebRTC"
Open a WebSocket connection to stream text and receive synthesized audio in real time. Authentication is provided via the standard Authorization: Bearer header. Send JSON frames with text to synthesize; receive JSON frames containing base64-encoded audio chunks.
GET /text-to-speech/speech
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/text-to-speech/speech"
Generate synthesized speech audio from text input. Returns audio in the requested format (binary audio stream, base64-encoded JSON, or an audio URL for later retrieval). Authentication is provided via the standard Authorization: Bearer header.
POST /text-to-speech/speech
Optional: aws (object), azure (object), disable_cache (boolean), elevenlabs (object), language (string), minimax (object), output_type (enum: binary_output, base64_output), provider (enum: aws, telnyx, azure, elevenlabs, minimax, rime, resemble), resemble (object), rime (object), telnyx (object), text (string), text_type (enum: text, ssml), voice (string), voice_settings (object)
curl \
-X POST \
-H "Authorization: Bearer $TELNYX_API_KEY" \
-H "Content-Type: application/json" \
"https://api.telnyx.com/v2/text-to-speech/speech"
Returns: base64_audio (string)
Retrieve a list of available voices from one or all TTS providers. When provider is specified, returns voices for that provider only. Otherwise, returns voices from all providers.
GET /text-to-speech/voices
curl -H "Authorization: Bearer $TELNYX_API_KEY" "https://api.telnyx.com/v2/text-to-speech/voices"
Returns: voices (array[object])
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
Convert PyTorch AT_DISPATCH macros to AT_DISPATCH_V2 format in ATen C++ code. Use when porting AT_DISPATCH_ALL_TYPES_AND*, AT_DISPATCH_FLOATING_TYPES*, or other dispatch macros to the new v2 API. For ATen kernel files, CUDA kernels, and native operator implementations.
Write docstrings for PyTorch functions and methods following PyTorch conventions. Use when writing or updating docstrings in PyTorch code.
Take team-telnyx/telnyx-ai-inference-curl from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.