Intent Classification

The Intent Classification Layer is the first gate every request passes through. It determines what the user is trying to accomplish, a quick autocomplete, a code review, a multi-file refactor, or a creative writing task, and tags the request with semantic intent metadata that downstream layers use for routing decisions.

Why It Matters

Not all LLM requests are equal. A “write me a React component” request needs a different provider, model, and budget than a “explain this error” request. Intent classification ensures Layerr doesn’t treat a five-minute coding task the same as a deep reasoning session.

Core Concepts

Concept	Description	Key File
Intent Signal	A typed classification of what the request is asking for	routing/types.ts
Classification Confidence	How certain the classifier is about its decision	workflow/classifier.ts
Workflow Style	Whether the task is agentic, interactive, batch, or streaming	workload/signals.ts
Routing Prompt	The assembled prompt sent to the routing engine	routing/prompt-builder.ts

The Classification Pipeline

Raw Request
    |
    v
[1] Extract Text Signals  --> urgency keywords, tool keywords, complexity cues
    |
    v
[2] Classify Workflow    --> classifyWorkflow() in workflow/classifier.ts
    |
    v
[3] Build Routing Prompt  --> routing/prompt-builder.ts
    |
    v
[4] Enrich Decision       --> enrichRoutingDecision() in routing/enrichment.ts

Signal Extraction

The system extracts signals from the request text to infer intent. Key signal types:

Urgency Signals

• High urgency: “fix now”, “urgent”, “broken”, “error”, “crash”
• Low urgency: “explain”, “review”, “when you have time”, “draft”

Tool Usage Prediction

• Agentic style: “create a file”, “run tests”, “deploy”, “execute”
• Interactive style: “what is”, “how do”, “explain why”
• Batch style: “refactor all”, “migrate every”, “batch process”

Complexity Signals

• Simple: “hello”, “quick question”, “one-liner”
• Medium: “component”, “function”, “small script”
• Complex: “architecture”, “system design”, “multi-file”, “review entire codebase”

File Reference

File	What It Does
workflow/classifier.ts	Main classification entrypoint. Parses request text, returns intent classification with confidence scores
routing/prompt-builder.ts	Assembles the routing prompt from classified intent + workload context
routing/types.ts	Type definitions for intent signals, routing decisions, and strategy selectors
workload/signals.ts	Signal extraction helpers, urgency, cost sensitivity, latency sensitivity

Integration with Downstream Layers

The intent classification feeds directly into:

1. Workload Analysis, the classified intent is combined with file-context signals to build a workload profile
2. Strategy Engine, intent determines which strategy (cost, speed, quality, balanced) is most appropriate
3. Provider Scoring, intent signals weight the scoring dimensions (e.g., coding intent prioritizes code-capable models)
4. Explainability, the classified intent appears in routing explanations so users understand why a model was chosen

Guardrails

• Confidence threshold: Classifications below a confidence floor are marked uncertain and trigger conservative routing (balanced strategy, premium provider)
• Ambiguity fallback: Multi-intent requests (e.g., “explain and fix”) are split or routed to the most capable model
• Workspace override: Workspace profiles can pin specific intents to specific strategies (e.g., “always use speed for autocompletes”)