- Add opening message instruction to atlas prompt
- Handle isInit flag in atlasChat() to not store the greeting trigger
as a user turn in conversation history
- Update server.ts to pass is_init through to atlasChat()
Made-with: Cursor
Layer 1 — src/agents/ (thin agent definitions, no prompt text)
registry.ts — AgentConfig, registerAgent(), getAgent(), AGENTS proxy, pick()
orchestrator.ts, coder.ts, pm.ts, marketing.ts — one file each, just metadata + tool picks
index.ts — barrel: imports prompts then agents (correct registration order)
Layer 2 — src/prompts/ (prompt text separated from agent logic)
loader.ts — registerPrompt(), resolvePrompt() with {{variable}} substitution
orchestrator.ts, coder.ts, pm.ts, marketing.ts — prompt templates as registered strings
orchestrator.ts now uses resolvePrompt('orchestrator', { knowledge }) instead of
inline SYSTEM_PROMPT const; {{knowledge}} variable injects project memory cleanly.
agent-runner.ts uses resolvePrompt(config.promptId) per agent turn.
Layer 3 — src/tools/skills.ts (new skills capability)
list_skills(repo) — lists .skills/<name>/SKILL.md directories from a Gitea repo
get_skill(repo, name) — reads and returns the markdown body of a skill file
Orchestrator and all agents now have get_skill in their tool sets.
Orchestrator also has list_skills and references skills in its prompt.
Also fixed:
- server.ts now passes history + knowledge_context from request body to orchestratorChat()
(these were being sent by the frontend but silently dropped)
- server.ts imports PROTECTED_GITEA_REPOS from tools/security.ts (no more duplicate)
- Deleted src/agents.ts (replaced by src/agents/ directory)
Made-with: Cursor
- ToolContext gets memoryUpdates[] — accumulated by save_memory calls
- orchestratorChat accepts preloadedHistory and knowledgeContext opts
- History trimmed to last 40 messages per turn (cost control)
- Knowledge items injected into system prompt as ## Project Memory
- ChatResult returns history[] and memoryUpdates[] for frontend persistence
- server.ts accepts history/knowledge_context from POST body
- save_memory tool: lets AI persist facts (key, type, value) to long-term memory
Made-with: Cursor
