Use this agent for Metabase Clojure backend work on the module system itself — adding new modules, splitting/merging modules, configuring `.clj-kondo/config/modules/config.edn`, resolving circular dependencies, designing module APIs, deciding where code should live (`.core` vs `.api` vs `.init` vs `.models.*`), interpreting module-score reports, or applying the modularization rules from Cam's Backend Modularization 2025 Plan. This agent is orthogonal to feature-domain experts: route here when the question is about module *organization*, not the feature inside the module. Examples: - user: "I'm adding a new notifications-v2 module — where do my settings, tasks, and event handlers go?" assistant: "Let me use the modules-backend-expert agent to lay out the `.settings`/`.task.*`/`.events.*`/`.init` namespaces and the `metabase-enterprise.core.init` wiring." <commentary>Module skeleton and init wiring. Use the modules-backend-expert agent.</commentary> - user: "The kondo linter says my module isn't allowed to use `metabase.permissions.core/can-read?` — it's not in the `:api` set" assistant: "Let me use the modules-backend-expert agent to read the current config, run `dev.deps-graph/print-kondo-config-diff`, and decide whether to add the dep to `:uses` or refactor the call out." <commentary>Module linter config and dep declaration. Use the modules-backend-expert agent.</commentary> - user: "I have a circular dep between `transforms` and `channel` — `transforms` calls a sender in `channel` and `channel` reads a setting from `transforms`" assistant: "Let me use the modules-backend-expert agent to redesign this with the event subsystem (publish `:event/transform-failed` from transforms; channel subscribes) so neither module depends on the other." <commentary>Circular dep resolution via events. Use the modules-backend-expert agent.</commentary> - user: "How small is small enough for `.core`? My module has 40 re-exports and reviewers are complaining" assistant: "Let me use the modules-backend-expert agent to run `dev.module-score/info`, identify which exports are actually used externally, and propose a smaller surface." <commentary>API surface review using module-score tooling. Use the modules-backend-expert agent.</commentary> - user: "Should this be one `permissions` module or two — `data-permissions` and `collection-permissions`?" assistant: "Let me use the modules-backend-expert agent to apply the granularity heuristic — separate libraries test, no circular deps, distinct user-facing concepts — and recommend an answer." <commentary>Module granularity decision. Use the modules-backend-expert agent.</commentary> - user: "I want to add `:clj-kondo/ignore` to silence one warning so I can ship this fix today" assistant: "Let me use the modules-backend-expert agent — suppression is explicitly forbidden by the modularization plan; we need to find the underlying refactor (move the setting, expand `:api`, or use the event bus) instead." <commentary>Pushing back on linter-cheating shortcuts. Use the modules-backend-expert agent.</commentary> - user: "I added a `defsetting` to my module but it's not appearing on the FE — what did I miss?" assistant: "Let me use the modules-backend-expert agent to check whether your `<module>.settings` namespace is required by `<module>.init`, and `<module>.init` by `metabase.core.init`." <commentary>Init-namespace wiring for settings/tasks/events. Use the modules-backend-expert agent.</commentary> - user: "Which tests should CI run if I only changed `src/metabase/search/`?" assistant: "Let me use the modules-backend-expert agent to run `dev.deps-graph/source-filenames->relevant-test-filenames` and explain the leaf-vs-upstream calculus." <commentary>Selective-CI reasoning via the dep graph. Use the modules-backend-expert agent.</commentary>

Use this agent for Metabase Clojure backend work on database driver system, metadata sync, schema introspection, fingerprinting, field value caching, or driver-specific behavior. This includes adding or modifying database drivers, fixing JDBC metadata issues, debugging sync processes, working with the driver multimethod hierarchy, type mapping between databases and Metabase's internal type system, connection management, SSH tunneling, DDL operations, or the plugin/lazy-loading system. Examples: - user: "Snowflake introduced a new GEOGRAPHY column type that we need to support" assistant: "Let me use the drivers-and-sync-backend-expert agent to add the type mapping in the Snowflake driver and ensure sync, fingerprinting, and the QP all handle it correctly." <commentary>Adding a new column type requires driver type mapping, sync detection, and QP compatibility. Use the drivers-and-sync-backend-expert agent.</commentary> - user: "Sync is taking hours for a customer with 10,000+ tables" assistant: "Let me use the drivers-and-sync-backend-expert agent to profile the sync pipeline, identify bottlenecks in describe-fields, and design a batched approach." <commentary>Sync performance at scale is core drivers-and-sync-backend-expert territory. Use the agent to diagnose and optimize.</commentary> - user: "We need to add a DuckDB driver" assistant: "Let me use the drivers-and-sync-backend-expert agent to scaffold the driver module, determine which multimethods need overriding, and build the integration tests." <commentary>New driver development requires deep understanding of the driver hierarchy and extension points. Use the drivers-and-sync-backend-expert agent.</commentary> - user: "The MySQL driver is returning wrong types for UNSIGNED BIGINT columns" assistant: "Let me use the drivers-and-sync-backend-expert agent to trace the type mapping from JDBC metadata through the sync pipeline and identify where the type coercion goes wrong." <commentary>Database-specific type mapping issues in the sync/driver layer. Use the drivers-and-sync-backend-expert agent.</commentary> - user: "Connection pooling is leaking connections when SSH tunnels drop" assistant: "Let me use the drivers-and-sync-backend-expert agent to examine the SSH tunnel lifecycle and connection pool integration." <commentary>Connection management and SSH tunneling are driver infrastructure concerns. Use the drivers-and-sync-backend-expert agent.</commentary>

Use this agent for Metabase Clojure backend work on AI features — Metabot, LLM integrations, tool calling, context engineering, the agent API, SQL generation/fixing, entity analysis, or dashboard/question description generation. This includes building or modifying Metabot tools, optimizing context selection for LLM calls, debugging tool calling behavior, working with the Anthropic API integration, managing conversation state, or implementing new AI-powered features. Examples: - user: "Metabot is generating SQL that misunderstands column semantics" assistant: "Let me use the ai-backend-expert agent to improve the table metadata context to include semantic annotations and sample values." <commentary>LLM context quality for SQL generation. Use the ai-backend-expert agent.</commentary> - user: "We need to add a new Metabot tool for creating filters" assistant: "Let me use the ai-backend-expert agent to implement the tool using the deftool macro with proper schema, permissions, and LLM-friendly descriptions." <commentary>Metabot tool implementation. Use the ai-backend-expert agent.</commentary> - user: "Context window is overflowing for tables with 200+ columns" assistant: "Let me use the ai-backend-expert agent to build relevance-aware context selection that prioritizes fields based on the query." <commentary>Context engineering and token management. Use the ai-backend-expert agent.</commentary> - user: "The LLM is calling the wrong tool or providing malformed parameters" assistant: "Let me use the ai-backend-expert agent to implement validation, error recovery, and retry logic for tool calls." <commentary>Tool calling reliability. Use the ai-backend-expert agent.</commentary> - user: "We need to expose Metabase capabilities as tools for external AI agents" assistant: "Let me use the ai-backend-expert agent to work on the agent API endpoint design." <commentary>Agent API for external tool use. Use the ai-backend-expert agent.</commentary>

Use this agent for Metabase Clojure backend work on query processor (QP), MBQL query language, SQL compilation, driver system, middleware pipeline, Lib, metadata providers, or streaming execution. This includes debugging query compilation issues, adding new MBQL clauses, fixing database-specific SQL generation bugs, working with HoneySQL, tracing middleware behavior, understanding preprocessing/postprocessing stages, working with transducers and reducibles in the QP, extending driver multimethods, or reasoning about cross-cutting concerns like permissions, sandboxing, and caching within the query pipeline.\n\nExamples:\n\n- user: "A nested query with joins is producing wrong results on Redshift but works on Postgres"\n assistant: "Let me use the mbql-backend-expert agent to trace this through the QP middleware pipeline and identify where join alias rewriting may be conflicting with Redshift's scoping rules."\n <commentary>Since this involves debugging query compilation across database dialects through the middleware pipeline, use the mbql-backend-expert agent to diagnose and fix the issue.</commentary>\n\n- user: "I need to add window function support as a new MBQL clause"\n assistant: "Let me use the mbql-backend-expert agent to design the MBQL schema extension, plan the preprocessing middleware, and implement HoneySQL compilation across drivers."\n <commentary>Adding a new MBQL clause requires deep understanding of the full QP pipeline — schema, preprocessing, compilation, and per-driver customization. Use the mbql-backend-expert agent.</commentary>\n\n- user: "Large result sets are consuming too much memory on this code path"\n assistant: "Let me use the mbql-backend-expert agent to trace the transducer chain and find where eager evaluation is breaking the streaming guarantee."\n <commentary>This involves the streaming execution model with reducibles and transducers. Use the mbql-backend-expert agent to identify and fix the memory issue.</commentary>\n\n- user: "How does the date bucketing middleware work? I need to modify temporal bucketing for a Snowflake edge case."\n assistant: "Let me use the mbql-backend-expert agent to examine the temporal bucketing middleware and understand how it interacts with Snowflake's driver-specific SQL compilation."\n <commentary>Understanding and modifying QP middleware behavior for a specific driver requires deep QP and driver system knowledge. Use the mbql-backend-expert agent.</commentary>\n\n- user: "I need to understand how source card resolution works in preprocessing"\n assistant: "Let me use the mbql-backend-expert agent to trace through the source card resolution middleware and explain the preprocessing flow."\n <commentary>Source card resolution is a core QP preprocessing middleware. Use the mbql-backend-expert agent to explain and navigate it.</commentary>\n\n- user: "The HoneySQL output for this CASE expression is wrong on Oracle"\n assistant: "Let me use the mbql-backend-expert agent to examine how the CASE expression compiles through HoneySQL and identify Oracle-specific compilation issues."\n <commentary>SQL compilation issues across dialects are core mbql-backend-expert territory. Use the agent to trace and fix the HoneySQL compilation.</commentary>

Use this agent for Metabase Clojure backend work on platform infrastructure — the application database, HTTP server, API framework, settings system, task scheduling, migration system, caching, model infrastructure, or core utilities. This includes debugging migration issues, modifying the Ring middleware stack, working with the settings system, extending the API framework (defendpoint, OpenAPI), managing connection pools, Quartz scheduling, Toucan 2 model patterns, or the utility libraries (HoneySQL helpers, Malli schemas, date/time, i18n, encryption). Examples: - user: "A custom migration needs to restructure a JSON column across 500K rows without downtime" assistant: "Let me use the platform-backend-expert agent to design a batched migration with progress tracking and resumability." <commentary>Application database migrations at scale. Use the platform-backend-expert agent.</commentary> - user: "The settings cache has a race condition in multi-instance deployments" assistant: "Let me use the platform-backend-expert agent to redesign the cache coherence protocol." <commentary>Settings cache infrastructure. Use the platform-backend-expert agent.</commentary> - user: "API response times are degrading under load" assistant: "Let me use the platform-backend-expert agent to profile the middleware stack and identify the bottleneck." <commentary>HTTP server and middleware performance. Use the platform-backend-expert agent.</commentary> - user: "We need a new Malli schema feature for API parameter validation" assistant: "Let me use the platform-backend-expert agent to implement it in the util.malli layer." <commentary>API framework and Malli integration. Use the platform-backend-expert agent.</commentary> - user: "How do streaming responses work for large query exports?" assistant: "Let me use the platform-backend-expert agent to explain the streaming response infrastructure and thread pool management." <commentary>Server streaming response architecture. Use the platform-backend-expert agent.</commentary> - user: "The Liquibase migration is failing on MySQL but works on PostgreSQL" assistant: "Let me use the platform-backend-expert agent to examine the database-specific migration logic." <commentary>Liquibase migration compatibility across app DB backends. Use the platform-backend-expert agent.</commentary>