Skip to main content

Crate roboticus_agent

Crate roboticus_agent 

Source
Expand description

§roboticus-agent

Agent core for the Roboticus runtime. The central module is agent_loop (mapped from loop.rs), which implements a ReAct reasoning loop as a typed state machine: Think → Act → Observe → Persist, with idle/loop detection and financial guards.

§Key Types

§Modules

  • context – Progressive context loading (4 levels) and compression
  • injection – 4-layer prompt injection defense
  • prompt – System prompt builder with HMAC trust boundaries
  • memory – Memory budget manager and turn ingestion
  • retrieval – Hybrid search RAG pipeline with content chunking
  • knowledge – KnowledgeSource trait and aggregation
  • discovery – Capability discovery across tools, skills, plugins
  • digest – Turn digest and history summarization
  • device – Device context and hardware info
  • workspace – Workspace state (file tree, git status, project metadata)
  • orchestration – Multi-agent task decomposition
  • governor – Rate governor and concurrency limits
  • typestate – Compile-time valid state transitions
  • speculative – Parallel branch evaluation with best-result selection
  • manifest – Agent capability declarations
  • services – Service locator and dependency wiring
  • mcp – Model Context Protocol client integration
  • wasm – WASM plugin runtime
  • obsidian / obsidian_tools – Vault integration and read/write/search tools
  • skills / script_runner – Skill loading, execution, sandboxed scripts
  • analyzer / recommendations – Conversation analysis and proactive suggestions

Modules§

action_planner
Deterministic action planner for task-oriented turns.
agent_loop
analyzer
approvals
capability
Unified capability registry — a catalog of invocable tools with metadata and dispatch.
compaction
Context compaction — minimize the token footprint of all injected context.
consolidation
Memory consolidation pipeline — the “dreaming” cycle.
context
device
digest
discovery
governor
ingest
Document ingestion pipeline: file -> parse -> chunk -> embed -> store.
injection
interview
knowledge
learning
Learning loop — detect successful multi-step tool sequences from completed sessions and synthesize reusable skill documents.
manifest
mcp
mcp_handler
MCP Server Handler — bridges rmcp’s ServerHandler to Roboticus’s ToolRegistry.
memory
normalization
Normalization
obsidian
obsidian_tools
orchestration
policy
prompt
ranking
Unified ranking types for memory retrieval and tool search convergence.
recommendations
retrieval
retrieval_strategy
Adaptive source discovery — policy-driven retrieval strategy selection.
script_runner
services
skills
speculative
subagents
task_state
Task Operating State — introspection-driven state synthesis.
tool_output_filter
Tool output noise filter — cleans tool output before it reaches the LLM.
tool_search
Semantic tool search — rank and prune tools before presenting to the LLM.
tools
topic
Topic segmentation for session conversation threads.
typestate
wasm
workspace