roadmap.md

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Roadmap

Phase 1 — Core DSL (in progress)

• Agent<IN, OUT> with SRP enforcement
• Agent.prompt — base context string for the LLM
• Skills-only execution — all agents run through skills { implementedBy { } }
• Skill.description — sells the skill to the LLM alongside its type signature
• Skill.knowledge("key", "description") { } — named lazy context providers; loadFile() inside lambdas
• Skill.toLlmDescription() — auto-generated markdown (name, types, description, knowledge index); llmDescription("...") override
• Skill.toLlmContext() — full context: description markdown + all knowledge content
• Skill.knowledgeTools() / KnowledgeTool(name, description, call) — tools model with lazy per-entry loading
• then — sequential pipeline with composed execution (no runtime casts)
• / — parallel fan-out with coroutine concurrency
• * — forum shorthand with concurrent participants, last-agent captain, and onMentionEmitted
• forum { participant(...); captain(...); allowForumReturn(...) } — explicit forum roles and finalization permissions
• Single-placement enforcement across all structure types
• .loop {} — iterative execution with (OUT) -> IN? feedback block
• .branch {} — conditional routing on sealed types, composable with then
• @Generable("desc") / @Guide / @LlmDescription — runtime reflection: toLlmDescription(), jsonSchema(), promptFragment(), fromLlmOutput<T>(), PartiallyGenerated<T>
• model { } — Ollama backend; host, port, temperature; injectable ModelClient for tests; auto-fallback to inline JSON tool-call format for models without native tool support (#706)
• Agentic execution loop — multi-turn tool calling with budget controls (maxTurns, maxToolCalls, maxDuration, perToolTimeout, maxTokens, maxConsecutiveSameTool) + onToolUse observability hook (#637, #963, #969)
• Skill selection — manual skillSelection {} + automatic LLM routing when multiple skills match
• onError { Throwable -> } — infrastructure-error observability hook (LLM transport, response parse, budget); pure observability — original exception always rethrows (#962)
• Agent.observe { event -> } — sealed PipelineEvent bridges the four hooks (skill / tool / knowledge / error) into one typed stream; composes additively (#965)
• Agent.toString() + Agent.describe() — readable single-line + multi-line debug output replacing the JVM identity-hash default (#970)
• onBudgetThreshold(threshold) { reason, usedPercent -> } — pre-cap warning hook; fires once per BudgetReason when cumulative usage crosses the fraction, before the cap throws (#966)
• loadResource(path) / loadResourceOrNull(path) — read agent system prompts from classpath resources; fail-fast at agent construction when path is missing; UTF-8 decoded; leading-slash normalized (#980)
• >> — security/education wrap

Phase 2 — Runtime + Distribution (Q2 2026)

Priority:

• Tool<IN, OUT> hierarchy + McpTool<IN, OUT> — MCP as native Tool inheritance, not a wrapper
• MCP client integration — McpTool instances consumable alongside local tools
• grants { tools(...) } — Layer 2 permissions use actual Tool<*,*> references
• Permission model: 3 states — Granted (auto-runs), Confirmed (user approval), Absent (unavailable)
• KSP annotation processor — compile-time @Generable; constrained decoding (Ollama) + guided JSON mode (Anthropic/OpenAI)
• Native CLI binary (GraalVM — no JRE required); brew, npm, pip, curl, apt
• jlink minimal JRE bundle for runtime (~35MB)

Secondary:

• Session model — multi-turn AgentSession, automatic compaction (SUMMARIZE, SLIDING_WINDOW, CUSTOM)
• Reactive context hooks — beforeInference, afterToolCall (context-mutating)
• Agent memory — MemoryBank, memory_read/memory_write/memory_search auto-injected tools
• .spawn {} — independent sub-agent lifecycle, AgentHandle<OUT>, parent-managed join
• Flow<PipelineEvent> for reactive UIs + Pipeline-level events (StageStarted, PipelineCompleted, etc) — depends on streaming, sub-agents, sessions
• Serialization — agent.json, A2A AgentCard
• JAR bundles and folder-based assembly
• Gradle plugin

Phase 3 — Production (Q3 2026)

• Layer 2: Full Structure DSL with delegates, grants, authority, routing, escalation
• All 37 compile-time validations enforced by Gradle plugin
• AgentUnit testing framework — unit, semantic (LLM-as-judge), Skill Coverage metrics
• A2A protocol support (server + client)
• File-based knowledge: skill.md, reference, examples, checklist + RAG pipeline
• Production observability: OpenTelemetry traces
• Team DSL — swarm coordination (if isolated execution available)

Phase 4 — Ecosystem (Q4 2026)

• Knowledge packs — battle-tested prompt libraries for common domains
• Agent generation from natural language (NL → Kotlin DSL)
• Skillify — extract reusable skills from session transcripts
• Visual structure editor, UML bidirectional conversion
• Knowledge marketplace

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