Espressif Systems avatar

Espressif Systems

Official

@espressif · Shanghai, China

0Followers
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328Public Repos
|
27Published Skills

Offers edge-computing capabilities for IoT hardware, enabling neural network execution, sensor integration, and device-level event management.

Skills Distribution
DomainCloud & Comp...Edge-Computing & IoT (40%)Neural Network Opt.. (30%)Embedded Systems P.. (30%)

Agent Skills by Espressif Systems

Showing 27 vetted skills indexed across 2 GitHub repositories.

espressifespressif
1.1k

esp32p4-simd

Converts scalar code into ESP32-P4 PIE SIMD assembly for neural network operators.

Official
Advanced
espressifespressif
1.1k

ESP32-S3 PIE SIMD Optimization

Converts scalar C loops into ESP32-S3 PIE SIMD assembly using EE.* instructions.

Official
Advanced
espressifespressif
1.1k

espdl-quantize

Automates iterative esp-ppq quantization tuning to recover accuracy on ESP-DL models.

Official
Advanced
espressifespressif
2.1k

ble

Control ESP-Claw BLE advertising, connections, and GATT services via Lua scripts.

Official
Advanced
espressifespressif
2.1k

scheduled_task

Creates cron and interval scheduled tasks for agent wake-ups, IM messages, and Lua script runs.

Official
Intermediate
espressifespressif
2.1k

plan_mode

Generates executable plans when requests exceed current agent capabilities or hardware resources.

Official
Intermediate
espressifespressif
2.0k

cap_llm_inspect_image

Inspect local image files and generate natural-language descriptions.

Official
Basic
espressifespressif
2.0k

cap_im_platform

Deliver text, images, or local files to Feishu, QQ, Telegram, or WeChat chats.

Official
Intermediate
espressifespressif
2.0k

cap_scheduler

Manage IoT device scheduler rules for timed event publications.

Official
Intermediate
espressifespressif
2.0k

cap_web_search

Search the internet via Tavily or Brave and return numbered results with titles, URLs, and snippets.

Official
Basic
espressifespressif
2.0k

cap_http_request

Retrieve HTTP status and body text from allowlisted endpoints.

Official
Intermediate
espressifespressif
2.0k

cap_time

Return the current local device date, time, weekday, and timezone.

Official
Basic
espressifespressif
2.0k

cap_router_mgr

Manage IoT event router automation rules via capability calls.

Official
Intermediate
espressifespressif
2.0k

skills_lab_search

Search the ESP-Claw Skills Lab hub by keywords and filters for skill ids.

Official
Intermediate
espressifespressif
2.0k

skills_lab_downloader

Download ESP-Claw skill packages and validate hardware compatibility before installation.

Official
Intermediate
espressifespressif
2.0k

skill_creator

Create or update model-invoked skills with SKILL.md and register_skill.

Official
Advanced
espressifespressif
2.0k

take_picture

Capture a JPEG image from a board camera via Lua script execution.

Official
Intermediate
espressifespressif
2.0k

ble_hid

Advertise an ESP-Claw composite HID device and send keyboard, mouse, and media reports.

Official
Intermediate
espressifespressif
2.0k

http_server_lua_demo

Serve a Hello World web UI with toggle state via Lua HTTP endpoints.

Official
Basic
espressifespressif
2.0k

read_touch

Read smoothed capacitive touch sensor values from specified GPIO channels.

Official
Basic
espressifespressif
2.0k

profile_memory_ops

Edit durable profile markdown documents for persona, identity, role, and style.

Official
Intermediate
espressifespressif
2.0k

memory_ops

Store, recall, list, update, and forget structured memory facts on-device.

Official
Intermediate
espressifespressif
2.0k

scheduled_task

Schedule cron or interval tasks for agent wake-ups, messages, and Lua scripts.

Official
Intermediate
espressifespressif
2.0k

weather_search

Search the web for current weather, temperature, and forecast queries.

Official
Basic

Frequently Asked Questions About Espressif Systems

FAQPage Schema
What specific tasks can I perform with Espressif's edge capabilities?

You can execute neural network operators, manage capacitive touch sensor inputs, control GPIO-based lighting, and handle BLE-HID peripheral communication directly on embedded hardware.

Which engineers should utilize these edge-computing capabilities?

Embedded systems engineers, IoT firmware developers, and machine learning practitioners focused on deploying optimized neural network models to resource-constrained hardware platforms.

What are the prerequisites for running these on-device programs?

Execution requires compatible Espressif hardware, the ESP-Claw environment for package management, and the Lua runtime for handling on-device logic and GPIO interactions.