sno

Execute the plan in parallel waves. Independent tasks run as concurrent agents, dependent tasks wait.

Verify the work matches the spec. Run tests, review changes, check acceptance criteria.

Quick mode for small tasks. Skip the full ceremony — describe what you want, get it done.

Understand the problem. Launch parallel research agents (Opus) for domain analysis, data modeling, and codebase scouting. Then interview for gaps. Produce a spec in .sno/spec.md.

Start a new sno cycle. Pulls latest, creates a branch, and initializes .sno/ state.

Use this agent during sno:plan to identify antipatterns, gotchas, and common mistakes for the specific tech stack and domain. Spawned by the plan command to run in parallel with the planner. <example> Context: User runs the plan command after learning phase is complete user: "/sno:plan" assistant: "I'll spawn parallel plan agents including the antipattern detector." <commentary> The plan phase benefits from proactive identification of antipatterns and gotchas specific to the tech stack and domain so the plan avoids known pitfalls. </commentary> </example>

Use this agent during sno:learn to explore the existing codebase for patterns, conventions, dependencies, and relevant existing code. Spawned by the learn command to run in parallel with other research agents. <example> Context: User is starting a new sno learn cycle in an existing project user: "/sno:learn" assistant: "I'll spawn parallel research agents including the codebase scout to understand what exists." <commentary> The learn phase needs to understand the existing codebase before writing a spec. </commentary> </example> <example> Context: User wants to add a feature to an existing codebase user: "Add webhook support to the API" assistant: "Let me scout the codebase to understand the current API structure and patterns." <commentary> Adding to existing code requires understanding what's already there. </commentary> </example>

Use this agent during sno:plan AFTER the draft plan is assembled to perform a critical review — checking for gaps, inconsistencies, missed risks, and spec drift. Runs after all other plan agents complete. <example> Context: Draft plan has been assembled from planner and other agent outputs user: (internal — spawned by plan command after draft is ready) assistant: "Running critical review on the draft plan before presenting to the user." <commentary> The critical reviewer is the final gate before the plan is shown to the user. It catches what the individual agents missed. </commentary> </example>

Use this agent during sno:learn to analyze data structures, relationships, and normalization. Designs toward 5NF. Spawned by the learn command to run in parallel with other research agents. <example> Context: User is starting a new sno learn cycle user: "/sno:learn" assistant: "I'll spawn parallel research agents including the data modeler to analyze data structures and relationships." <commentary> The learn phase needs data modeling to understand storage requirements before writing a spec. </commentary> </example> <example> Context: User describes entities with relationships user: "Users can have multiple organizations and each org has projects" assistant: "Let me model the data relationships and normalize to 5NF." <commentary> Multi-entity relationships require proper normalization analysis. </commentary> </example>

Use this agent during sno:learn to research the problem domain, identify bounded contexts, aggregates, and ubiquitous language using Domain-Driven Design principles. Spawned by the learn command to run in parallel with other research agents. <example> Context: User is starting a new sno learn cycle for a feature user: "/sno:learn" assistant: "I'll spawn parallel research agents including the domain researcher to analyze the problem space." <commentary> The learn phase needs deep domain understanding before writing a spec. This agent handles the DDD analysis. </commentary> </example> <example> Context: User describes a new system to build user: "We need a billing system that handles subscriptions and usage-based pricing" assistant: "Let me research the billing domain — bounded contexts, aggregates, and entities." <commentary> Complex domain requires DDD analysis to identify boundaries and language before planning. </commentary> </example>