LLM ORCHESTRATOR

Overview 01 Plan First 02 Route Intelligently 03 Execute & Learn

Prompt Optimization LayerTune prompts so cheaper models match production quality.Hybrid Model ArchitectureExpensive orchestrator delegates to cheap sub-agents. No wasted spend on simple tasks.Smart Model SelectionAuto-picks the best model per prompt, using expensive models only when needed.Model Limitation AwarenessKnows model limits — escalates or reroutes instead of hallucinating.

Granular Plan ModeGenerates detailed step-by-step plans when needed, and skips planning for simple tasks.Pre-Execution Token EstimationSee token usage and projected cost before build commands run.Token Budgeting SystemSet token budgets per session, task, or team — enforced before compute runs.Structured Plan OutputOutputs interactive plan.html — reviewable decisions, not markdown walls.

Smart Context ManagementOnly pass context relevant to the latest prompt — not the full session history.Context & Memory ControlAdd or remove context and memory to control what the model sees.

Interactive Think ModePause, redirect, or correct the agent mid-run — no full restart.Skill BuilderBuild skills with test and evaluation modes to benchmark and fine-tune behavior.CLI + Local Web IDEProvides a terminal CLI and localhost web IDE with embedded chat.AI Collaboration ModeShared agent sessions and handoffs — break out of solo AI silos.

Cross-User LearningIndexes resolved failures org-wide, like Stack Overflow for AI agent runs.Automatic Repository RulesGenerates repo rules from your codebase patterns on init.

All capabilities

Capability

Smart Model Selection

Auto-pick the best model based on the prompt.

Summary

Auto-picks the best model per prompt, using expensive models only when needed.

The problem

Engineers pick a default model and never change it — overpaying on simple tasks and underpowering complex ones.

How Devtor solves it

Devtor analyzes each prompt for complexity, domain, and required reasoning depth, then selects the minimum viable model from your configured provider pool.

Benefits

Automatic model selection per task type
Expensive models reserved for high-complexity work
Explainable routing logs for every run
No manual model switching per prompt

Use cases

Mixed workloads from quick lookups to architecture design
Multi-provider setups with different price tiers
Teams without time to tune model defaults per task

Part of the orchestration flow

Route Intelligently

Right model. Right price.

PreviousSmart Context Management

NextPre-Execution Token Estimation

Ready to orchestrate?

Installation guide and CLI — coming soon.