stim-simulator
Clifford circuit simulation skill using Stim for error correction studies
Profile →npx skills add a5c-ai/babysitter --skill stim-simulator --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Stim Simulator ## Purpose Provides expert guidance on fast stabilizer circuit simulation using Stim, enabling large-scale quantum error correction studies and noise analysis. ## Capabilities - Fast stabilizer circuit simulation - Error injection and propagation - Detector sampling - Circuit tableau tracking - Memory-efficient large-scale simulation - Monte Carlo error rate estimation - Detector error model generation - Pauli frame simulation ## Usage Guidelines 1. **Circuit Construction**: Build Stim circuits with appropriate gates and noise 2. **Detector Definition**: Specify detectors for syndrome measurement 3. **Sampling**: Generate detector samples for decoding analysis 4. **Error Model**: Extract detector error models for decoder training 5. **Statistics**: Collect sufficient samples for statistical significance ## Tools/Libraries - Stim - Stimcirq - PyMatching - NumPy
- Purpose
- Capabilities
- Usage Guidelines
- Tools/Libraries
What does the stim-simulator skill do?
Clifford circuit simulation skill using Stim for error correction studies
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill stim-simulator --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.