feat(backends): multi-backend intelligence layer — LLM + Agent backends, persona-loading agents, honest CLI commands
Add IntelligenceBackend abstraction with two categories: - LLMBackend (OllamaLocal, OllamaCloud): CI runs tool loop, provides tools, constructs prompts - AgentBackend (Opencode): agent runs own tool loop, CI serializes request Refactor all 18 agents from hardcoded stubs to persona loaders that delegate to the active backend or fail honestly when no backend is available. Refactor OrchestratorAgent.executeStage() from monolithic switch to agent delegation via STAGE_AGENT_MAP for intelligent stages (research, plan, execute, verify), with mechanical stages (specify, clarify, complete) staying inline. Wire CLI commands with --backend flag and auto-detection (opencode → ollama-local → ollama-cloud). Harden rollback/ship with real git operations. No command returns fake success.
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@@ -3,17 +3,26 @@ import { BaseAgent, AgentContext, AgentResult } from "./base.js";
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export class PlannerAgent extends BaseAgent {
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readonly name = "planner";
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readonly description = "Creates phase plans with tasks. Never sets autonomous:false — decomposes into verifiable subtasks.";
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readonly workflow = "plan";
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async execute(context: AgentContext): Promise<AgentResult> {
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this.log("Creating phase plan...");
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const start = Date.now();
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this.log("Creating phase plan...");
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if (context.backend) {
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const result = await this.executeViaBackend(
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context,
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`Create a phase plan for stage ${context.stage}, phase ${context.phase}. Specification: ${context.specification}`
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);
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return { ...result, duration_ms: Date.now() - start };
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}
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return {
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success: true,
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output: "Plan created with verifiable subtasks",
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artifacts_created: ["PLAN.md"],
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decisions: 1,
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success: false,
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output: "Planning requires an intelligence backend. Configure one with: ci init --backend",
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artifacts_created: [],
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decisions: 0,
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escalations: 0,
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duration_ms: Date.now() - start,
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error: "No intelligence backend available",
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};
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}
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}
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