jenkinsm13

Bump the package version in pyproject.toml and publish to PyPI. Handles version increment, git tag, build, and upload in one step.

Project conventions and patterns for resolve-mcp development. Explains tool registration, error handling, module organization, and naming rules.

AI-powered color grading assistant. Exports the current frame in sRGB, visually analyzes it, and makes CDL adjustments directly on the Color page nodes. Works regardless of project color space (HDR, P3, ACES, etc.) because the frame is converted to sRGB for analysis — the color space LLMs are trained on.

Match the color grade of the current DaVinci Resolve timeline frame to a reference image. Exports both in sRGB, visually compares them, and adjusts CDL nodes to match the reference look.

Archive a DaVinci Resolve project — export the .drp project file, media list, timeline markers, render queue status, and editorial notes as a complete archive package.

Paste timecoded client feedback or review notes and auto-create color-coded markers on the DaVinci Resolve timeline at each timecode.

Render multiple deliverables from one DaVinci Resolve timeline in a single batch — YouTube, Instagram, broadcast, ProRes master, etc.

Full pre-delivery QC check on the current DaVinci Resolve timeline — runs timeline audit and color consistency check together, then summarizes all issues.

Guide UV mapping, texture atlas generation, color calibration, and texture quality optimization in Metashape MCP. Covers blending modes, ghosting filter, texture size selection by use case, and diagnosing common texture artifacts. Works through the Metashape MCP server.

Export all available products from the current Metashape project — point cloud, model, DEM, orthomosaic, tiled model, report, and cameras. Skips unavailable products automatically.

Diagnose alignment quality issues in the current Metashape project — checks camera alignment rate, tie point density, reprojection error, and sensor calibration. Provides actionable fix recommendations.

Recommend optimal Metashape processing settings based on dataset size and available RAM. Provides specific parameter values for each processing step with quality/speed trade-offs.

Download USGS 3DEP LiDAR DEM data, colorize with satellite imagery, and import into Metashape as laser scan ground truth. Use when extending photogrammetry environments with surrounding terrain.

Guide dense reconstruction, mesh building, and texturing in Metashape MCP. Covers depth maps, point cloud, mesh, texture, DEM, and orthomosaic generation with correct GPU/CPU settings and quality parameters. Works through the Metashape MCP server.

Set up a new Metashape project from scratch — import photos, load GPS reference, configure sensors (fisheye, rolling shutter, multi-camera), import EXR alpha masks, run image quality analysis, and disable bad frames. The first skill to use on any new capture. Works through the Metashape MCP server.

Prevent and remove sky/tunnel mesh artifacts in road corridor photogrammetry. Covers five strategies from Metashape-side prevention (height field, region crop, point cloud classification, source selection) to post-mesh cleanup. The

Batch FBX export with game-engine golden rules, pre-export checklist, and post-export verification.

Export cleaned meshes from Blender to Metashape for re-texturing, then import the textured result back.

Full 6-phase terrain cleanup pipeline for photogrammetry tiles - assessment, cleanup, envelope, classification, UV, optimization.

Step-by-step verification of PLY tile imports from Metashape - naming, transforms, bounding boxes, and grid coverage.

Bump patch version, build, publish to PyPI, commit, and push to GitHub

Project conventions and patterns for resolve-assistant development