Results for “epss”
15 skills
More results
mesteriis esp32
Applies ESP32 rules for GPIO, boot states, relays, sensors, connectivity, firmware safety, and validation.
0
mesteriis esphome
Applies safe ESPHome rules for YAML, lambdas, sensors, switches, relays, boot behavior, fail-safes, and validation.
0
ssrjkk esp32
Programs ESP32 microcontrollers in C/C++ or MicroPython. Use for IoT projects with WiFi/Bluetooth.
2 · bundle
tradermonty stockbee-episodic-pivot-analyzer
Analyzes Stockbee-style Day 1 Episodic Pivot candidates by scoring catalyst quality alongside price/volume confirmation, gap/range expansion, volume shock, neglect/revaluation context, liquidity, and risk to the EP-day low.
2.3k · bundle
tianhao909 sparse-autoencoder-training
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
1 · bundle
enuno polar-strategy
POLAR v2.0 — ETH Alpha Hunter. The patience benchmark. Thesis exit permanently removed. Scanner enters, DSL exits. +19.8% ROE trades after removing thesis exit.
1 · bundle
agentskillexchange eslint-rule-composer
Creates custom ESLint rules using the ESLint RuleTester API and AST Explorer patterns, generating rule implementations with auto-fix suggestions based on estree node types and scope analysis.
28
orchestra-research sparse-autoencoder-training
Train and analyze Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features for mechanistic interpretability research.
10.4k · bundle
ssrjkk esp-idf
Programs ESP32 microcontrollers using ESP-IDF framework with FreeRTOS, Wi-Fi, and Bluetooth.
2 · bundle
aibot88 esql
ES|QL Query Skill
3 · bundle
chen-yu-hao pyopenms
Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.
5 · bundle
bobmatnyc espocrm
Comprehensive guide for developing on EspoCRM - metadata-driven CRM with service layer architecture
71 · bundle
a5c-ai epic-generation
Epic Generation
1.7k · bundle
qcmuu sparse-autoencoder-training
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
0 · bundle