AI DevKit · Publish a ready feature branch for review. Use when the user wants to sync, push, and open or update a code review request on GitHub, GitLab, or another Git host.

AI DevKit · Planning phase guidance for creating and reconciling feature task plans. Use when the user wants to create an implementation plan, update planning docs, mark task progress, capture blockers or new tasks, or run dev-lifecycle planning work.

AI DevKit · Orchestrator for structured SDLC phase skills. Use when the user wants to run the full lifecycle or choose the next phase across requirements, design, planning, implementation, testing, and review.

AI DevKit · Implementation phase guidance for executing feature plans and checking implementation against design. Use when the user wants to implement planned tasks, update implementation docs, verify code matches design, or run dev-lifecycle phases 5 and 7.

AI DevKit · Design phase guidance for reviewing feature design against requirements. Use when the user wants to validate architecture, review design docs, resolve design trade-offs, or run dev-lifecycle phase 3.

AI DevKit · Safe git commit workflow for AI coding agents. Use when the user asks to commit, prepare a commit, stage changes, create a PR-ready checkpoint, or finish work with a conventional commit while avoiding unrelated user changes.

AI DevKit · Update CHANGELOG.md Unreleased items from git commits since the latest release. Use when users ask to update changelog/release notes from recent commits, with one concise line per commit and commit/PR links.

AI DevKit · Supervise multi-agent workflows over repeated passes: poll progress, unblock waiting agents, coordinate dependencies, relay outputs, resolve conflicts, and verify completion. Use only for ongoing multi-agent coordination, not one-off list/detail/send/start/kill actions.

AI DevKit · Manage running AI agents with ai-devkit agent commands. Use when an agent needs to identify itself, list agents, start workers, inspect agent detail, assign work, group agents, resume sessions, stop agents, or delegate work to other agents.

AI DevKit · Exchange information with active Codex, Claude Code, and other AI agents using ai-devkit agent list, detail, and send. Use when an agent needs to find another active agent, read its recent context, send it information, or request information back.

Rust OpenTelemetry style for Maple: opentelemetry + opentelemetry_sdk + opentelemetry-otlp HTTP exporter, tracing-opentelemetry bridge for the tracing crate, inline endpoint + ingest key, semconv resource attributes.

Python OpenTelemetry style for Maple: module-scope tracers/meters, decorators for bounded work, error spans, OTLP-bridged logs via LoggingHandler + LoggingInstrumentor, inline endpoint + ingest key, and no helper-API wrappers.

Review a diff, PR, or specific file in this repo for OpenTelemetry *specification* compliance, grounded in the source-linked spec corpus at docs/otel-spec/ (snapshot v1.58.0). Triggers on requests like 'is this spec compliant', 'review this PR against the OTel spec', 'spec-review this diff', 'check my partial-success handling', 'are these retryable status codes right', 'does apps/ingest honor the OTLP spec', and on reviews of changes touching the OTLP server surface in apps/ingest (partial success, retryable set {429, 502, 503, 504}, protobuf Status bodies, gzip, OTLP/JSON encoding), self-instrumentation (apps/api tracer setup, apps/ingest/src/otel.rs, packages/effect-sdk), or consumers of span status / SeverityNumber / db.query.text (WarehouseQueryService, query-engine). Spec MUSTs and SHOULDs only — for Maple house conventions use maple-telemetry-conventions; for whole-project instrumentation audits use maple-audit; for general diff correctness use /code-review.

Onboard a project to Maple by installing OpenTelemetry traces, logs, and metrics across every app and service in the repo. Triggers on requests like 'install Maple', 'set up Maple', 'add Maple telemetry', 'onboard this repo to Maple', 'instrument with OpenTelemetry for Maple'.

General OpenTelemetry onboarding style for Maple: native APIs, signal quality, inline keys, VCS resource attributes, LLM metrics, and smoke checks.

Plain Node.js (Express, Fastify, Hono, Bun) OpenTelemetry style for Maple: NodeSDK + --import bootstrap, native @opentelemetry/api call sites, inline endpoint + ingest key, OTLP HTTP exporters.

Next.js / Vercel OpenTelemetry style for Maple: instrumentation.ts, @vercel/otel bootstrap, native @opentelemetry/api call sites, inline endpoint + ingest key, no raw NodeSDK replacement.

Kotlin (Ktor, Spring Boot) OpenTelemetry style for Maple: zero-code Java agent or manual SDK with OTLP HTTP exporters, inline endpoint + ingest key, semconv resource attributes, OTLP-bridged logs.

Java OpenTelemetry style for Maple: zero-code Java agent or manual SDK with OTLP HTTP exporters, inline endpoint + ingest key, semconv resource attributes, OTLP-bridged Logback / SLF4J logs.

Go OpenTelemetry style for Maple: go.opentelemetry.io/otel SDK with otlptracehttp / otlploghttp / otlpmetrichttp exporters, inline endpoint + ingest key, semconv resource attributes including vcs.repository.url.full.