cli-anything-cloudanalyzer

Command-line interface for CloudAnalyzer — Agent-friendly harness for CloudAnalyzer, a QA platform for mapping, localization, and perception outputs. Supports 27 commands across 8 groups: point cloud evaluation, trajectory evaluation, ground segmentation QA, config-driven quality gates, baseline evo

By hkuds · 397 installs

npx skills add hkuds/cli-anything --skill cli-anything-cloudanalyzer

Source repository · Upstream listing

cli anything cloudanalyzer Agent friendly command line harness for [CloudAnalyzer](https://github.com/rsasaki0109/CloudAnalyzer) — a QA platform for mapping, localization, and perception point cloud outputs. 27 commands across 8 groups. Installation Prerequisites: Python 3.10+ CloudAnalyzer: pip install cloudanalyzer Global Options Option Description p, project TEXT Path to project JSON file json Output results as JSON (for agent consumption) Command Groups 1. evaluate — Point Cloud Evaluation (6 commands) evaluate run Evaluate a point cloud against a reference (Chamfer, F1, AUC, Hausdorff). Options: plot TEXT , threshold FLOAT evaluate compare Compare two point clouds with optional registration. Options: register TEXT (icp/gicp/none) evaluate diff Quick distance statistics between two point clouds. evaluate batch Batch evaluation of multiple point clouds against a reference. Options: min auc FLOAT , max chamfer FLOAT evaluate ground Evaluate ground segmentation quality (precision, recall, F1, IoU). Options: voxel size FLOAT , min precision FLOAT , min recall FLOAT , min f1 FLOAT , min iou FLOAT evaluate pipeline Filter, downsample, evaluate in one command. 2. trajectory — Trajectory Evaluation (3 commands) trajectory evaluate Evaluate estimated vs reference trajectory (ATE, RPE, drift, lateral, longitudinal). Options: max ate FLOAT , max rpe FLOAT , max drift FLOAT , min coverage FLOAT , max lateral FLOAT , max longitudinal FLOAT , align origin , align rigid trajectory batch Batch trajectory evaluation. trajectory run evaluate Integrated map + trajectory evaluation. Options: min auc FLOAT , max ate FLOAT 3. check — Config Driven Quality Gate (2 commands) check run Run unified QA from a config file. Options: output json TEXT check init Generate a starter config file. Options: profile TEXT (mapping/localization/perception/integrated), force 4. baseline — Baseline Evolution (3 commands) baseline decision Decide whether to promote, keep, or reject a candidate baseline. Options: history TEXT (repeatable), history dir TEXT , output json TEXT baseline save Save a QA summary to the history directory. Options: history dir TEXT , label TEXT , keep INTEGER baseline list List saved baselines. 5. process — Point Cloud Processing (6 commands) process downsample Voxel grid downsampling. process sample Random point sampling. process filter Statistical outlier removal. process split Split point cloud into grid tiles (writes metadata.yaml). process merge Merge multiple point clouds. process convert Convert between point cloud formats. 6. inspect — Visualization (3 commands) inspect view Open a point cloud viewer. inspect web Interactive browser inspection. inspect web export Export a static HTML inspection bundle. 7. info — Metadata (2 commands) info show Show point cloud metadata. info version Show CloudAnalyzer version. 8. session — Session Management (2 commands) session new Create a new harness project JSON file. session history Show recent operations for the project given with p / project . Typical Agent Workflows Workflow 1: Evaluate and gate a point cloud Workflow 2: Config driven QA pipeline Workflow 3: Baseline management Workflow 4: Ground segmentation QA