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It provides an intelligent agent interface for discovering, executing, and analyzing quantum calibration experiments with support for automated workflows and vision-based analysis.","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FQuantum-Calibration-Agent-Blueprint\u002Ftree\u002FHEAD\u002Fdata\u002Fknowledge\u002Fskills\u002Fexperiment-execution","---\nname: experiment-execution\ndescription: Reference guide for running individual quantum calibration experiments and interpreting their results. Use when the user asks to run a single experiment (e.g. resonator spectroscopy, qubit spectroscopy, T1, T2), inspect experiment plots with the VLM, or query experiment history and schemas via the lab tool.\n---\n\n# Experiment Execution Guide\n\nReference guide for running and analyzing quantum calibration experiments.\n\n## Tools Available\n\n### run_experiment\nExecute a quantum calibration experiment.\n```python\nrun_experiment(\n    experiment_name=\"resonator_spectroscopy\",\n    params={\n        \"center_freq\": 6.0,\n        \"span\": 0.2,\n        \"num_points\": 101,\n        \"power\": -20,\n        \"num_averages\": 2000\n    }\n)\n```\nReturns: `{\"id\": \"...\", \"status\": \"success\", \"results\": {...}, \"plots\": [...]}`\n\n### vlm_inspect\nAI-powered visual analysis of experiment plots.\n```python\nvlm_inspect(\n    experiment_id=\"20240315_103015_resonator\",\n    prompt=\"Is there a clear dip? What is the resonator frequency and estimated SNR?\"\n)\n```\nReturns: Text analysis of the plot.\n\n### lab\nQuery experiment information and history.\n```python\nlab(action=\"schema\", experiment_name=\"resonator_spectroscopy\")  # Get parameter schema\nlab(action=\"history_show\", experiment_id=\"...\")                  # Get experiment details\nlab(action=\"get_stats\", experiment_id=\"...\", array_name=\"...\")  # Get array statistics\n```\n\n## ⚠️ Data Analysis Rules\n\n**NEVER copy raw experiment arrays into shell commands.** Large arrays will be truncated and cause syntax errors.\n\n**DO use these approaches:**\n1. **VLM analysis**: `vlm_inspect(experiment_id=..., prompt=\"...\")` - visual plot analysis\n2. **Returned scalars**: `run_experiment` returns fitted values like `resonator_freq`, `t2_star`, etc.\n3. **Lab stats**: `lab(action=\"get_stats\", experiment_id=..., array_name=\"...\")` for array statistics\n\n**DON'T do this:**\n```python\n# BAD - will fail with syntax errors\nexecute(\"python3 -c 'data = [0.1, 0.2, 0.3, ...]'\")  # Arrays too long!\n```\n\n## Standard Execution Flow\n\n1. **Run experiment** with appropriate parameters\n2. **Get experiment_id** from result\n3. **Display results** - ALWAYS include this tag in your response:\n   `\u003Cexperiment experiment-id=\"THE_EXPERIMENT_ID\" \u002F>`\n   (Replace THE_EXPERIMENT_ID with the actual ID. This shows the interactive viewer with plots.)\n4. **Analyze plots** with vlm_inspect - ask about peaks, dips, resonances, SNR\n5. **Extract values** from VLM analysis (frequency, linewidth, SNR)\n6. **Verify success criteria** if defined\n7. **If failed, adjust and retry** (up to max attempts)\n\n## Verifying Success Criteria\n\nAfter running an experiment, verify results against success criteria when applicable.\n\n### When to Verify\n- **DO verify** when success criteria are defined in the workflow plan\n- **DO verify** when numeric thresholds need checking (SNR, linewidth, depth, etc.)\n- **SKIP verification** if user has already seen the plot and confirmed success\n- **SKIP verification** if no specific success criteria were provided\n\n### Verification Methods\n\n**Visual (VLM):** Use `vlm_inspect` to analyze plots\n- Ask specific questions matching the criteria\n- Example: \"Is there a single clear peak? What is the SNR? Is it greater than 5?\"\n- Example: \"Is there a visible dip with depth > 3 dB?\"\n\n**Programmatic:** Check returned data values directly\n- Extract values from experiment results (e.g., `snr`, `peak_frequency`, `linewidth`)\n- Compare against thresholds in success criteria\n\n## Typical Parameter Ranges\n\n| Experiment | Parameter | Typical Range |\n|------------|-----------|---------------|\n| qubit_spectroscopy | start\u002Fstop | 4500-5500 MHz |\n| qubit_spectroscopy | step | 0.5-10 MHz |\n| qubit_spectroscopy | num_avs | 500-5000 |\n| resonator_spectroscopy | start\u002Fstop | 6000-8000 MHz |\n| resonator_spectroscopy | step | 0.1-1 MHz |\n\n## Success\u002FFailure Indicators\n\n### Good Data (Success)\n- Clear single peak or dip visible\n- SNR >= 5 (ideally >= 8)\n- Peak width reasonable (5-50 MHz for qubit)\n- Smooth baseline, low noise\n\n### Bad Data (Retry Needed)\n- No visible peak\u002Fdip\n- Multiple peaks (ambiguous)\n- SNR \u003C 3\n- High noise floor\n- Saturation or clipping\n\n## Retry Strategies\n\nIf experiment fails, try these adjustments:\n\n1. **No peak found**: Expand frequency range (1.5x wider)\n2. **Low SNR**: Increase num_avs (2x more averaging)\n3. **Multiple peaks**: Narrow range around strongest peak\n4. **High noise**: Increase num_avs, check for interference\n\n## Example Execution\n\n```\nTask: Run resonator spectroscopy centered at 6.0 GHz\n\nAttempt 1:\n> run_experiment(experiment_name=\"resonator_spectroscopy\",\n                 params={\"center_freq\": 6.0, \"span\": 0.2, \"num_points\": 101, \"num_averages\": 2000})\n> Result: experiment_id = \"20240315_103015_resonator\"\n> Include in response: \u003Cexperiment experiment-id=\"20240315_103015_resonator\" \u002F>\n> vlm_inspect(experiment_id=\"20240315_103015_resonator\",\n              prompt=\"Is there a clear dip? What is the frequency and SNR?\")\n> VLM: \"Clear dip visible at 5.823 GHz. Estimated SNR ~12. Clean baseline.\"\n\nSuccess! 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Trigger keywords - nemoclaw docs, use nemoclaw with ai agent, nemoclaw mcp docs, nemoclaw install help, nemoclaw quickstart, nemoclaw markdown docs, llms.txt, agent skills.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[996,999,1002],{"name":997,"slug":998,"type":15},"Documentation","documentation",{"name":1000,"slug":1001,"type":15},"MCP","mcp",{"name":1003,"slug":1004,"type":15},"Search","search",21777,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FNemoClaw","2026-07-20T06:00:01.461044",{"slug":1009,"name":1009,"fn":1010,"description":1011,"org":1012,"tags":1013,"stars":1021,"repoUrl":1022,"updatedAt":1023},"mcore-build-and-dependency","manage Megatron-LM development environments","Container-based dev environment setup and dependency management for Megatron-LM. 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Covers CI pipeline structure, PR scope labels, triggering internal GitLab CI (which force-pushes the current branch to a pull-request\u002FBRANCH ref — always dry-run and verify the destination first; never run against shared or protected branches), and CI failure investigation.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1041,1042,1043],{"name":1031,"slug":1032,"type":15},{"name":1018,"slug":1019,"type":15},{"name":1044,"slug":1045,"type":15},"GitHub","github","2026-07-27T06:06:12.278222",{"slug":1048,"name":1048,"fn":1049,"description":1050,"org":1051,"tags":1052,"stars":1021,"repoUrl":1022,"updatedAt":1060},"mcore-create-issue","investigate CI failures and create issues","Investigate a failing GitHub Actions run or job and create a GitHub issue for the failure.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1053,1056,1057],{"name":1054,"slug":1055,"type":15},"Debugging","debugging",{"name":1044,"slug":1045,"type":15},{"name":1058,"slug":1059,"type":15},"Triage","triage","2026-07-14T05:25:57.442089",{"slug":1062,"name":1062,"fn":1063,"description":1064,"org":1065,"tags":1066,"stars":1021,"repoUrl":1022,"updatedAt":1073},"mcore-linting-and-formatting","lint and format Megatron-LM code","Linting and formatting for Megatron-LM. 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