Template Management

💡 Upload and manage instruction files for AI-assisted development. Drop files in the Inbox, then reference filenames in chat to trigger builds.

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💡 Run context scans to understand the codebase at a glance. Each scan analyses a different aspect: system architecture, database tables, API endpoints, templates, and models.

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💡 Track development tasks through their lifecycle: Planned, In Progress, Implemented, Needs Testing, Tested, Verified, Released. Jobs require test evidence before verification.

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💡 Daily work log. Session activity is automatically logged here. Use "Enhance with AI" on entries to expand brief notes into detailed summaries.

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💡 View work history by date. Click "Close Out Today" to generate an AI-powered daily digest summarising what was accomplished.

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💡 User feedback and AI-generated suggestions scored by priority. Convert high-priority items into tracked Jobs for the development pipeline.

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💡 Reference guide for the Course Builder feature. Create custom training materials outside standard TGA units, with AI-powered conversational course design.

🎓 Course Builder FEATURE

🧠 Feature Overview

AI-powered course design and content generation pipeline for custom training materials outside TGA units. Organisations can design course outlines via AI conversation or manual entry, then generate full learner guides through the existing Stage C pipeline.

🔌 API Reference

Method	Path	Description
GET	/api/course-builder/outlines	List all outlines for org
POST	/api/course-builder/outlines	Create new outline
GET	/api/course-builder/outlines/{id}	Get outline with sections
PUT	/api/course-builder/outlines/{id}	Update outline metadata
DELETE	/api/course-builder/outlines/{id}	Delete draft outline
POST	/api/course-builder/outlines/{id}/sections	Add section
PUT	/api/course-builder/sections/{id}	Update section
DELETE	/api/course-builder/sections/{id}	Soft-delete section
POST	/api/course-builder/outlines/{id}/reorder	Reorder sections
POST	/api/course-builder/outlines/{id}/generate	Start generation pipeline
POST	/api/course-builder/conversations	Start AI design conversation
GET	/api/course-builder/conversations	List conversations
GET	/api/course-builder/conversations/{id}/messages	Get messages
POST	/api/course-builder/conversations/{id}/messages	Send message (triggers AI response)
POST	/api/course-builder/conversations/{id}/approve	Create outline from AI conversation
DELETE	/api/course-builder/conversations/{id}	Delete conversation
POST	/api/course-builder/outlines/{id}/tga-framework	Generate TGA framework for outline
GET	/api/course-builder/outlines/{id}/tga-framework	Get TGA framework data
GET	/api/course-builder/outlines/{id}/tga-framework/export	Export TGA framework as DOCX
POST	/api/course-builder/outlines/{id}/tga-proposal	Generate TGA proposal from framework
PATCH	/api/course-builder/outlines/{id}/branding	Update branding settings
POST	/api/course-builder/outlines/{id}/tga-research	Trigger TGA-specific research
GET	/api/course-builder/outlines/{id}/tga-research	Get TGA research results
PATCH	/api/course-builder/outlines/{id}/tga-research	Update TGA research decisions

⚙️ Pipeline Configuration

Feature Flag

course_builder — must be enabled per organisation via feature flags

Generation Pipeline

Course Builder runs skip Stage A/B. The blueprint is pre-built by the adapter, then goes straight to Stage C content generation.

AI Routing Stages

course_design — conversation AI for outline design
course_design_research — TGA-specific research framework for industry/regulatory context

Cost Tracking

All AI calls use cost_category="setup" and track via the unified AiUsageEvent system.

Adapter

app/services/course_builder_adapter.py converts CourseOutline → UnitBlueprint format for Stage C compatibility.

🗃️ Data Model

Table	Description
course_outlines	Main outline with metadata, status (draft → ready → generating → completed), AQF level, audience context, quality mode, `tga_proposal_enabled`, and `rpl_pack_enabled` flags
course_outline_sections	Sections with learning outcomes, key topics, content type (theory/practical/assessment), complexity hint, and word targets
course_design_conversations	AI design chat sessions linked to org/user, with context snapshot and status tracking
course_design_messages	Individual messages (user/assistant/system) with interactive elements, user selections, and token usage tracking

💡 Agent skill registry. Skills are reusable instructions that extend what the AI agent can do. Auto-scans from the .agents/skills/ directory.

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💡 Project health dashboard: codebase metrics, pipeline success rates, AI spend tracking, and security status. Click Refresh All to update.

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RTOFlow Development Roadmap

AI-powered training and compliance platform for Australian RTOs. Tracking progress from concept through to production scale.

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💡 SEO Master Plan tracker. Shows progress across all marketing and SEO initiatives, content coverage, and next priorities.

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💡 Quick-access shell commands for common operations. Click the copy button to copy a command, then paste it into the Replit Shell tab.

Shell Commands

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Push to GitHub

Staged push — auto-batches large pushes