القائمة
Generates 3D interior models from photos and injects them into Mapbox GL JS map instances.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | 3d-modeler |
| description | Generates 3D interior models from photos and injects them into Mapbox GL JS map instances. |
| version | 1.0.0 |
| author | Ahmed Qaddoura |
| dependencies | ["@lumaai/luma-web","three","threebox-plugin"] |
This skill allows agents to convert photographs of interiors into 3D models (GLB/GLTF) and inject them into web-based Mapbox 3D styles using Three.js and the Threebox plugin.
photoTo3D.js to call 3D reconstruction APIs (e.g., Luma AI / Polycam) to process an image and return a URL to a GLB file.mapboxInjector.js to prepare a GLB file for Mapbox insertion, calculating the necessary MercatorCoordinates and Three.js scale/rotation matrices to align the interior model perfectly with the real-world map.When a user uploads a photo of a room and asks to place it on the map, trigger this skill:
photoTo3D.js. Wait for the 3D generation to complete.mapboxInjector.js to get the integration payload.Generates dynamic video montages and edits video content for social distribution.
The cold-start protocol for an AI agent PICKING UP a handoff bundle (the receiving half of `handoff`). Triggers when a fresh session is pointed at a handoff directory or pasted a handoff block — e.g. "read this handoff", "take over from this bundle", "you're picking up <path>", "continue this work", or when the first message is a handoff block. Boots the agent loaded: reads the bundle README + manifest, runs Prime from it, confirms understanding and locked decisions BEFORE writing code, and refuses to start on a bundle with no manifest/mission. Works in any tool (Claude, Cursor, Copilot, Codex, Gemini, Aider, Windsurf).
The mandatory completion-report skill. When an agent finishes (or is blocked on) a handoff bundle or delegated task, it MUST write the outcome to files — never only into chat. Triggers on "I'm done", "this is shipped", "wrap up", "close out this task", "I'm blocked", or automatically at the end of any `handoff-receiver` / `execute` run. Writes a `<bundle>-shipped/handoff.md` report with a fixed schema (commit SHA, what shipped, files touched, test/smoke results, deferred items, new open questions) and sets the source bundle's `manifest.json` status to `shipped · <SHA>` or `blocked · <reason>`. This is the file-based feedback loop that lets a control plane track every agent across tools.
Lightweight mid-flight progress logging for long agent runs. Where `report-back` writes the final outcome, status-beacon drops short, timestamped progress notes to a file DURING the work so a human or orchestrator can check in without interrupting. Triggers on long/multi-phase tasks, or when the user says "keep a log", "leave progress notes", "beacon this", "let me track this". Appends to a `progress.md` inside the active bundle/work dir. Honest about uncertainty — notes are signals, not guarantees. Works across Claude, Cursor, Copilot, Codex, Gemini, Aider, Windsurf.
Captures insights, rules, and learnings from any AI coding conversation into the user's personal ai-doctrine.md file — a single source of truth that is then auto-synced into Claude Code, Cursor, Copilot, Codex, Gemini CLI, and Windsurf so every tool the user opens reads the same hard-won rules. Use this skill whenever the user says "add to doctrine", "save this rule", "capture this learning", "this should be a rule", "doctrine this", "remember this", or asks to record an insight from a prompt/response. Also triggers when the user shares a hard-won learning, a prompt pattern that worked unusually well, a failure mode to avoid, or any rule they want to remember across tools.
Delegates real work to a coding agent (Claude Code, Cursor agent mode, Codex, Aider) and tracks the run end-to-end. Triggers on "execute", "run agent", "ship this", "delegate this", "hand off to Claude Code". Creates a run reference, watches for completion signals, links output back into the conversation, and offers to save successful execution patterns to ~/ai-doctrine.md so the same delegation playbook works across every agentic tool the user has installed.