Agent skill · AI & Agents

rb-benchmarker

Randomized benchmarking skill for gate fidelity characterization

a5c-ai1,642★ · 1 repos on radarProfile →
claude-codecodexcan modify filesMIT
Install
npx skills add a5c-ai/babysitter --skill rb-benchmarker --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Allowed tools: -Bash-Read-Write-Edit-Glob-Grep
Path: library/specializations/domains/science/quantum-computing/skills/rb-benchmarker/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,642
Language: JavaScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# RB Benchmarker ## Purpose Provides expert guidance on randomized benchmarking protocols for characterizing quantum gate fidelities and hardware performance. ## Capabilities - Standard randomized benchmarking - Interleaved randomized benchmarking - Simultaneous RB for crosstalk - Character benchmarking - Cycle benchmarking - Fidelity decay fitting - SPAM error separation - Confidence interval estimation ## Usage Guidelines 1. **Protocol Selection**: Choose RB variant based on characterization goals 2. **Sequence Generation**: Create random Clifford sequences of varying lengths 3. **Execution**: Run benchmarking experiments with sufficient statistics 4. **Fitting**: Analyze decay curves to extract fidelity parameters 5. **Reporting**: Generate comprehensive benchmarking reports ## Tools/Libraries - Qiskit Experiments - Cirq - True-Q - PyGSTi - SciPy

What's inside
Steps it walks through
  1. Purpose
  2. Capabilities
  3. Usage Guidelines
  4. Tools/Libraries
More from babysitter
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About this skill
What does the rb-benchmarker skill do?

Randomized benchmarking skill for gate fidelity characterization

How do I install it?

Run `npx skills add a5c-ai/babysitter --skill rb-benchmarker --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.

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