architect
01Agent
Ask when consequential design choices must be settled before or during implementation — investigates context, compares approaches, and records decisions.
Experimental self-improving multi-agent coding system: a root agent recursively decomposes goals and delegates to specialist subagents, learning from failures by mutating a git-backed agent genome. Supports Claude, GPT, and Gemini.
Agent
Ask when consequential design choices must be settled before or during implementation — investigates context, compares approaches, and records decisions.
Agent
Memory investigation, synthesis, and authorized curation when surfaced memories are insufficient.
Agent
Systematically diagnose and fix bugs: find root cause before attempting any fix.
Agent
Observe Sprout's live session behavior and send concise guidance when it is drifting, stuck, or missing an important instruction.
Agent
Explore and understand unfamiliar codebases, map architecture, and synthesize structural insights.
Agent
Ask when you need to know what Sprout agents, tools, or MCP servers are available, need a reusable capability plan, or need a new specialist built; not for local command/runtime/cwd checks.
Agent
Build new specialist agent definitions on the fly.
Agent
Discover and index available capabilities across agents, tools, and MCP servers.
Agent
Plan how to accomplish goals by combining available tools, agents, and MCP capabilities.
Agent
Reconcile genome/root differences and propose contributions.
Agent
Analyze, search, debug, and repair Sprout sessions using metadata and JSONL event logs.
Agent
Diagnose whether Sprout is learning effectively from sessions, stumbles, metrics, and pending evaluations.
Agent
Explain Sprout internals and advise on changes using architecture resources plus source verification.
Agent
Manage the full implementation cycle for a single task: dispatch engineer, run two-stage review, iterate until approved.
Agent
Implement a single task from a plan: write code, write tests, commit, and report status.
Agent
Review implementation code quality: cleanliness, testing, maintainability, and design.
Agent
Review whether an implementation matches its task specification — nothing more, nothing less.
Agent
Private sidecar commentator for the human; watches root sessions without steering them.
Agent
Ask to run shell commands — build, test, install, git, or any CLI tool — and get back execution findings.
Agent
Ask to create named files or make targeted edits — acts directly when targets are decisive, reads only when context is missing.
Agent
Ask to interact with external services via MCP (Model Context Protocol) — list available servers, discover their tools, and call them with arguments.
Agent
Ask to manage project memory documents — list, read, write, or search .md files in the project memory directory.
Agent
Ask to find and read specific files or search for patterns — returns extracted information, not raw dumps. Use for quick targeted lookups, not broad exploration.
Agent
Ask to track work items for this session — create tasks, list them by status, update progress, assign to agents, and add comments.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: