القائمة
Interactive educational autograd engine — port of Karpathy's micrograd. Build, train, and visualise tiny neural networks step-by-step to learn how backpropagation works.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Sends messages between agents, broadcasts to channels, and retrieves message history for inter-agent communication.
Spawns, manages lifecycle, and terminates autonomous AI agents from the 40+ built-in agent catalog.
Optimize prompts and context windows to reduce token usage while preserving quality.
Animated desktop character state machine for Sven's Tauri companion app. Manages character form (ORB, ARIA, REX, ORION), state transitions (idle→thinking→speaking→celebrating), walk cycles, thought bubbles, sound effects, and real-time agent event sync.
Multi-model deliberation system. Sends queries to multiple LLMs simultaneously, has them peer-review each other's responses anonymously, then a chairman model synthesizes the best answer. Supports configurable council composition, voting strategies, and cost tracking.
Runs benchmark suites against models, tracks ELO rankings, manages A/B tests, and generates performance reports.
| name | micrograd |
| description | Interactive educational autograd engine — port of Karpathy's micrograd. Build, train, and visualise tiny neural networks step-by-step to learn how backpropagation works. |
| version | 0.1.0 |
| publisher | acmecorp |
| handler_language | typescript |
| handler_file | handler.ts |
| inputs_schema | {"type":"object","properties":{"action":{"type":"string","enum":["create_session","destroy_session","list_sessions","get_walkthrough_step","advance_walkthrough","create_model","train_model","train_with_snapshots","get_decision_boundary","generate_moon_dataset","get_stats"]},"session_id":{"type":"string"},"org_id":{"type":"string"},"step_index":{"type":"number"},"architecture":{"type":"array","items":{"type":"number"}},"dataset_type":{"type":"string","enum":["xor","moon","custom"]},"learning_rate":{"type":"number"},"epochs":{"type":"number"},"loss_function":{"type":"string","enum":["mse","hinge","bce"]},"seed":{"type":"number"},"snapshot_every":{"type":"number"},"custom_data":{"type":"object","properties":{"xs":{"type":"array"},"ys":{"type":"array"}}}},"required":["action"]} |
| outputs_schema | {"type":"object","properties":{"result":{"type":"object"}}} |
| tags | ["education","neural-networks","autograd","visualization"] |
Interactive educational autograd engine — a TypeScript port of Andrej Karpathy's micrograd.
| Action | Description |
|---|---|
create_session | Start a new micrograd learning session |
destroy_session | Clean up a session |
list_sessions | List active sessions (optionally filtered by org) |
get_walkthrough_step | Get a specific walkthrough step by index |
advance_walkthrough | Get the next walkthrough step in sequence |
create_model | Create an MLP with a given architecture |
train_model | Train a model on XOR, moon, or custom data |
train_with_snapshots | Train with periodic snapshots for Canvas animation |
get_decision_boundary | Generate a 2D decision boundary grid |
generate_moon_dataset | Generate a moons classification dataset |
get_stats | Engine statistics |
