Claude Skills by MapleTechLabs

Drop-in pandas replacement with ClickHouse performance. Use `import chdb.datastore as pd` (or `from datastore import DataStore`) and write standard pandas code — same API, 10-100x faster on large datasets. Supports 16+ data sources (MySQL, PostgreSQL, S3, MongoDB, ClickHouse, Iceberg, Delta Lake, etc.) and 10+ file formats (Parquet, CSV, JSON, Arrow, ORC, etc.) with cross-source joins. Use this skill when the user wants to analyze data with pandas-style syntax, speed up slow pandas code, quer...

In-process ClickHouse SQL engine for Python — run ClickHouse SQL queries directly on local files, remote databases, and cloud storage without a server. Use when the user wants to write SQL queries against Parquet/CSV/ JSON files, use ClickHouse table functions (mysql(), s3(), postgresql(), iceberg(), deltaLake() etc.), build stateful analytical pipelines with Session, use parametrized queries, window functions, or other advanced ClickHouse SQL features. Also use when the user explicitly menti...

MUST USE when designing ClickHouse architectures, selecting between ingestion or modeling patterns, or translating best practices into workload-specific system designs. Complements clickhouse-best-practices with decision frameworks and explicit provenance labels.

MUST USE when reviewing ClickHouse schemas, queries, or configurations. Contains 28 rules that MUST be checked before providing recommendations. Always read relevant rule files and cite specific rules in responses.

Use when a user wants to deploy ClickHouse to the cloud, go to production, use ClickHouse Cloud, host a managed ClickHouse service, or migrate from a local ClickHouse setup to ClickHouse Cloud.

Use when a user wants to build an application with ClickHouse, set up a local ClickHouse development environment, install ClickHouse, create a local server, create tables, or start developing with ClickHouse. Covers the full flow from zero to a working local ClickHouse setup.

Index of all COSS UI particle examples. Use when implementing UI features to find copy-paste-ready component patterns built on coss primitives. Each particle has a description and a JSON URL for easy installation.

Helps implement coss UI components correctly. Use when building UIs with coss primitives (buttons, dialogs, selects, forms, menus, tabs, inputs, toasts, etc.), migrating from shadcn/Radix to coss/Base UI, composing trigger-based overlays, or troubleshooting coss component behavior. Covers imports, accessibility, Tailwind styling, and common pitfalls.

Maple's OpenTelemetry conventions: custom span attribute keys (`maple.*` vendor namespace, `query.context`, `db.query.*`, `result.*`, `cache.*`, `tenant.*`), Title Case status codes (`Ok`/`Error`/`Unset`), resource attribute dual-emit (`deployment.environment` + `deployment.environment.name`), span kinds, Tinybird MV pre-extracted columns, loop-prevention filters, and sampling. Use whenever writing or reviewing instrumentation code in any language (TypeScript, Rust, Python) in this repo: addi...

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are...

Use when finishing a feature, fixing a bug, before committing React code, or when the user wants to improve code quality or clean up a codebase. Checks for score regression. Covers lint, dead code, accessibility, bundle size, architecture diagnostics.

Tinybird CLI commands, workflows, and operations. Use when running tb commands, managing local development, deploying, or working with data operations.

Tinybird Python SDK for defining datasources, pipes, and queries in Python. Use when working with tinybird-sdk, Python Tinybird projects, or data ingestion and queries in Python.

Tinybird TypeScript SDK for defining datasources, pipes, and queries with full type inference. Use when working with @tinybirdco/sdk, TypeScript Tinybird projects, or type-safe data ingestion and queries.

Tinybird file formats, SQL rules, optimization patterns, and best practices for datasources, pipes, endpoints, and materialized views.

Trace Agno agents with Maple: installs the OpenInference Agno instrumentor with an OTLP exporter and GenAI attributes, and sets session_id per conversation so each chat is one Maple Agent Session with transcript, tool calls, team members, tokens and cost. Triggers on 'trace my agno agent', 'add Maple to agno', 'agent sessions for agno', 'OpenTelemetry for agno'.

Trace Claude Agent SDK agents (TypeScript and Python) and Claude Code CLI sessions with Maple: configure Claude Code's built-in OpenTelemetry so each conversation becomes one Maple Agent Session with prompts, model calls, tool calls and tokens. Triggers on 'trace my claude agent sdk agent', 'add Maple to claude agent sdk', 'agent sessions for claude code', 'OpenTelemetry for claude agent sdk', 'send my claude code sessions to Maple'.

Trace Cloudflare Agents SDK agents (AIChatAgent, Agent on Durable Objects, npm `agents` / `@cloudflare/ai-chat`) with Maple: export the Vercel AI SDK's OpenTelemetry spans from a Worker/Durable Object over fetch, flush per turn, and pass the agent instance name as the conversation id so each chat is one Agent Session with transcript, tool calls, sub-agents and tokens. Triggers on 'trace my cloudflare agent', 'add Maple to cloudflare agents', 'agent sessions for AIChatAgent', 'OpenTelemetry in...

Trace CrewAI crews and flows with Maple: OpenInference CrewAI instrumentor plus the model-SDK instrumentor, GenAI dual-write, one Maple Agent Session per conversation with transcript, model and tool calls, tokens, failed tools and one lane per agent. Triggers on 'trace my crewai agent', 'add Maple to crewai', 'agent sessions for crewai', 'OpenTelemetry for crewai'.

Trace DSPy programs and ReAct agents with Maple: OpenInference DSPy instrumentor with GenAI dual-write, a DSPy callback for tokens, cost, tool names and agent spans, using_session for one session per conversation, and thread context for dspy.Parallel. Triggers on 'trace my dspy agent', 'add Maple to dspy', 'agent sessions for dspy', 'OpenTelemetry for dspy'.

Trace Genkit (TypeScript/Node.js) agents with Maple: export Genkit's OpenTelemetry spans to Maple, map its genkit:* attributes to the GenAI conventions with a span processor, and stamp a conversation id so each chat is one Agent Session with transcript, tool calls and tokens. Covers flows, ai.generate, generateStream and beta defineAgent chats. Triggers on 'trace my genkit agent', 'add Maple to genkit', 'agent sessions for genkit', 'OpenTelemetry for genkit', 'firebase genkit tracing'.

Trace Google ADK (Agent Development Kit) agents with Maple, in Python (google-adk) and TypeScript (@google/adk): register an OTLP tracer provider, get the transcript and tool calls into the GenAI attributes Maple reads (env switches + a plugin in Python, a span processor in TypeScript), and keep one session per ADK session id. Triggers on 'trace my ADK agent', 'add Maple to Google ADK', 'add Maple to @google/adk', 'agent sessions for Google ADK', 'OpenTelemetry for google-adk'.

Trace Haystack agents with Maple: installs a small Haystack tracer that adds OpenTelemetry GenAI attributes to Haystack's own spans, so each conversation is one Maple Agent Session with transcript, model, tokens, cost and tool failures. Triggers on 'trace my haystack agent', 'add Maple to haystack', 'agent sessions for haystack', 'OpenTelemetry for haystack'.

Trace LangChain and LangGraph agents (Python, and LangChain.js / LangGraph.js in TypeScript) with Maple: export OpenInference LangChain spans with GenAI attributes so each thread is one Maple Agent Session with transcript, tool calls, sub-agent lanes and tokens. Triggers on 'trace my langchain agent', 'trace my langgraph agent', 'add Maple to langchain', 'add Maple to langgraph', 'agent sessions for langchain', 'OpenTelemetry for langgraph', 'trace langchain.js', 'trace langgraph.js', 'create...

Trace LiteLLM agents with Maple: export LiteLLM's v2 OpenTelemetry spans (Python SDK or self-hosted LiteLLM Proxy) plus your own agent/tool spans so each conversation is one Maple Agent Session with transcript, tool calls, tokens and cost. Triggers on 'trace my litellm agent', 'add Maple to litellm', 'agent sessions for litellm', 'OpenTelemetry for litellm', 'trace the litellm proxy'.

Trace LlamaIndex agents with Maple: OpenInference LlamaIndex instrumentor with GenAI output, a conversation id per chat, agent names and one span per model call, so each conversation is one Maple Agent Session with transcript, tools and tokens. Triggers on 'trace my llamaindex agent', 'add Maple to llamaindex', 'agent sessions for llamaindex', 'OpenTelemetry for llamaindex', 'llama-index observability'.

Trace Mastra agents and workflows with Maple: export Mastra's built-in GenAI spans through @mastra/otel-exporter so each conversation is one Maple Agent Session with transcript, tool calls, sub-agent lanes and tokens. Triggers on 'trace my mastra agent', 'add Maple to mastra', 'agent sessions for mastra', 'OpenTelemetry for mastra'.

Trace Microsoft Agent Framework and Semantic Kernel agents (Python and .NET) with Maple: native GenAI spans exported over OTLP/HTTP, plus a span processor that adds the conversation id so each chat is one Agent Session with transcript, tools and tokens. Triggers on 'trace my agent framework agent', 'add Maple to Microsoft Agent Framework', 'add Maple to Semantic Kernel', 'agent sessions for agent-framework', 'OpenTelemetry for Semantic Kernel'.

Trace OpenAI Agents SDK agents with Maple: bridges the SDK's tracing to OpenTelemetry with OpenInference (GenAI attributes on), wraps each run in using_session so each chat is one Maple Agent Session with transcript, tool calls, handoffs, sub-agent lanes and tokens. TypeScript (@openai/agents) via the OpenInference JS bridge with gen_ai.conversation.id in context. Triggers on 'trace my openai agents sdk agent', 'add Maple to openai-agents', 'add Maple to @openai/agents', 'agent sessions for O...

Trace OpenRouter calls with Maple: route OpenRouter Broadcast (OTLP) to Maple and edit the app's OpenRouter requests to send session_id and trace ids, so each conversation is one Maple Agent Session with model calls, tokens and real cost. Triggers on 'trace my openrouter calls', 'add Maple to openrouter', 'agent sessions for openrouter', 'OpenTelemetry for openrouter', 'openrouter broadcast to maple'.

Trace a hand-rolled or unsupported AI agent with Maple by emitting the OpenTelemetry GenAI conventions yourself (invoke_agent, chat, execute_tool spans) in any language: TypeScript, Python, Go, Rust, Ruby, Elixir, Java, .NET. Triggers on 'trace my custom agent', 'add Maple to my agent loop', 'agent sessions without a framework', 'OpenTelemetry GenAI spans by hand', 'OpenTelemetry for my AI agent in Go/Rust/Ruby'.

Trace agents built directly on the OpenAI, Anthropic or Google Gen AI SDKs (Python or TypeScript, no agent framework) with Maple: official OTel GenAI instrumentations in Python, a small span helper in TypeScript, plus invoke_agent/execute_tool spans and gen_ai.conversation.id so each conversation is one Agent Session. Triggers on 'trace my openai agent', 'add Maple to my anthropic agent', 'agent sessions for gemini', 'OpenTelemetry for the openai sdk'.

Trace Pydantic AI agents with Maple: export Pydantic AI's built-in OpenTelemetry spans (with or without Logfire) so each conversation is one Maple Agent Session with transcript, tool calls, sub-agent lanes and tokens. Triggers on 'trace my pydantic ai agent', 'add Maple to pydantic ai', 'agent sessions for pydantic ai', 'OpenTelemetry for pydantic ai'.

Trace Hugging Face smolagents agents with Maple: OpenInference instrumentor with GenAI dual-write, one Maple Agent Session per conversation with transcript, model and tool calls, tokens, failed tools and managed-agent lanes. Triggers on 'trace my smolagents agent', 'add Maple to smolagents', 'agent sessions for smolagents', 'OpenTelemetry for smolagents'.

Trace Spring AI agents with Maple: wires Spring Boot's OpenTelemetry starter to Maple, samples every turn, and adds one configuration class so each ChatClient conversation is one Maple Agent Session with transcript, tool calls (failures marked), sub-agent lanes and tokens. Triggers on 'trace my spring ai agent', 'add Maple to spring ai', 'agent sessions for spring ai', 'OpenTelemetry for spring ai'.

Trace Strands Agents (AWS, Python or TypeScript) with Maple: export Strands' built-in OpenTelemetry spans with messages on span attributes, a session id per conversation and per-call token counts, so each conversation is one Maple Agent Session with transcript, tool calls, sub-agent lanes and tokens. Triggers on 'trace my strands agent', 'add Maple to strands', 'agent sessions for strands', 'OpenTelemetry for strands agents'.

Trace Vercel AI SDK agents with Maple: register the AI SDK's OpenTelemetry integration, export to Maple, and pass a conversation id so each chat is one Agent Session with transcript, tool calls, sub-agents and tokens. Covers generateText, streamText, ToolLoopAgent, Node.js and Next.js. Triggers on 'trace my vercel ai sdk agent', 'add Maple to vercel ai sdk', 'agent sessions for vercel ai sdk', 'OpenTelemetry for vercel ai sdk', 'trace my ai sdk app'.

Trace an AI agent or LLM app with Maple so each conversation shows up as one Agent Session with its transcript, model calls, tool calls, tokens, cost and failures. Detects the agent framework (Vercel AI SDK, OpenAI Agents SDK, Mastra, LangChain/LangGraph, Claude Agent SDK, Pydantic AI, LlamaIndex, CrewAI, Google ADK, Strands, smolagents, Agno, DSPy, Haystack, Microsoft Agent Framework, Spring AI, LiteLLM, OpenRouter, raw provider SDKs) and installs the matching per-framework skill. Triggers o...

Audit an already-instrumented project against Maple's OpenTelemetry conventions, report gaps per service, and fix them. Triggers on requests like 'audit my instrumentation', 'check my telemetry', 'review my OTel setup', 'why is my service map missing edges', 'is my Maple instrumentation correct'.

.NET / C# OpenTelemetry style for Maple: OpenTelemetry.Extensions.Hosting + OTLP HTTP exporter, ActivitySource for spans, ILogger bridging via WithLogging, inline endpoint + ingest key.

Build, repair, or review Maple dashboard widgets via the MCP. Triggers on phrases like 'create_dashboard', 'add_dashboard_widget', 'update_dashboard_widget', 'dashboard widget JSON', 'panel_type', 'QueryDraft', or any session that submits widget JSON to the maple MCP. Covers the panel-type table, the kind-discriminated data source, the percent vs percent_100 unit rule, valid aggregations and group-by tokens per source, the custom whereClause grammar, the scalar reduceToValue transform, and th...

Effect-TS OpenTelemetry style for Maple via @maple-dev/effect-sdk: Maple.layer() bootstrap, Effect.withSpan / Effect.annotateCurrentSpan call sites, Effect.log for trace-correlated logging, server / browser / Cloudflare entry points.

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.

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.

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.

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, @maple-dev/browser on the client.

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.

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, the business-span pattern, signal quality, inline keys, VCS resource attributes, LLM calls, and smoke checks.

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 su...