neatlogs-ingest

Plugin neatlogs-ingest from marketplace neatlogs in neatlogs/skills. Commands read from the repo's manifest — 6 days ago.

Skills (23)

• neatlogs-go

  Use when adding neatlogs observability to a Go project — Google Gemini (genai), Google ADK, direct LLM/provider calls, retrieval, service boundaries, or custom code. Covers Init, WrapGenAI, the private-provider ADK integration, explicit span helpers, Trace, and Identify.

• neatlogs-ingest

  Use when sending traces to Neatlogs from a language without a supported Neatlogs SDK, or when configuring direct HTTP ingest, OTLP/gRPC, an OpenTelemetry exporter, or an OpenTelemetry Collector. Defaults unsupported languages to POST /v1/trace nested JSON and documents the separate OTLP transports.

• neatlogs-local-testing

  Test and improve a user's real agent with the Neatlogs CLI and SDK. Create or resume local experiments, capture or select dataset cases, run current and candidate versions with quality checks, and compare recorded evidence in Neatlogs.

• neatlogs-multi-workflow

  Language-agnostic guidance for instrumenting a codebase that runs MULTIPLE independent workflows/features in one process (e.g. a copilot + a summarizer + a background job) with neatlogs, so each shows up as a distinct, filterable workflow in the dashboard. Use this in addition to the language skill

• neatlogs-public-api-cli

  Use when reading NeatLogs traces or managing a cloud project through the supported Public API or neatlogs-cli. Covers project-scoped authentication, CLI commands, safe trace readback, pagination, and the boundary between SDK ingest and public reads.

• neatlogs-py-agno

  Use when adding neatlogs observability to a Python project that uses the Agno agent framework (imports `agno`, constructs Agno `Agent`s).

• neatlogs-py-crewai

  Use when adding neatlogs observability to a Python project that uses CrewAI (imports `crewai`, builds a Crew/Flow with agents and tasks).

• neatlogs-py-dspy

  Use when adding neatlogs observability to a Python project that uses DSPy (imports `dspy`, defines `dspy.Module`s / signatures).

• neatlogs-py-google-adk

  Use when adding neatlogs observability to a Python project that uses the Google Agent Development Kit (imports `google.adk`, builds an ADK agent/runner).

• neatlogs-py-hermes

  Use when adding neatlogs observability to a Python project that uses the Hermes agent (NousResearch/hermes-agent) as a LIBRARY — i.e. it imports `run_agent` / constructs `AIAgent(...)` in its own code.

• neatlogs-py-langchain

  Use when adding neatlogs observability to a Python project that uses LangChain or LangGraph (imports `langchain*` / `langgraph`, builds chains, runnables, or a graph).

• neatlogs-py-openai-agents

  Use when adding neatlogs observability to a Python project that uses the OpenAI Agents SDK (imports `agents` / `openai-agents`, defines `Agent`s and calls `Runner.run`).

• neatlogs-py-openai

  Use when adding neatlogs observability to a Python project that calls LLM provider SDKs directly (OpenAI, Anthropic, Google GenAI, Groq, etc.) and uses no agent framework.

• neatlogs-py-pydantic-ai

  Use when adding neatlogs observability to a Python project that uses Pydantic AI (imports `pydantic_ai`, constructs an `Agent`).

• neatlogs-py-setup

  Use when adding neatlogs observability to a Python LLM/agent project and no framework-specific neatlogs skill matches the stack — i.e. the generic fallback for instrumenting Python apps that call LLMs or run agents.

• neatlogs-py-strands

  Use when adding neatlogs observability to a Python project that uses Strands Agents (imports `strands`, builds a Strands `Agent`).

• neatlogs-py

  NeatLogs is an AI agent debugging and observability platform. Use this skill when instrumenting Python LLM applications with neatlogs for tracing, monitoring, debugging, observability, decorators, spans, or instrumentation of LLM providers and agent frameworks.

• neatlogs-ts-langchain

  Use when adding neatlogs observability to a TypeScript/Node.js project that uses LangChain or LangGraph (depends on `@langchain/*` / `@langchain/langgraph`).

• neatlogs-ts-mastra

  Use when adding neatlogs observability to a TypeScript/Node.js project that uses the Mastra framework (depends on `@mastra/core`, builds a Mastra agent/workflow).

• neatlogs-ts-openai

  Use when adding neatlogs observability to a TypeScript/Node.js project that calls LLM provider SDKs directly (OpenAI, Anthropic, Google GenAI, Bedrock) and uses no agent framework.

• neatlogs-ts-pi-agent

  Use when adding neatlogs observability to a TypeScript/Node.js project that uses maintained `@earendil-works/pi-agent-core` / `@earendil-works/pi-ai` or legacy `@mariozechner` Pi packages, including `Agent`, `AgentHarness`, functional loops, and standalone stream functions.

• neatlogs-ts-vercel-ai

  Use when adding neatlogs observability to a TypeScript/Node.js project that uses the Vercel AI SDK (depends on the `ai` package, calls `generateText`/`streamText`).

• neatlogs-ts

  NeatLogs is an AI agent debugging and observability platform. Use this skill when instrumenting TypeScript/Node.js LLM applications with neatlogs for tracing, monitoring, debugging, observability, spans, or instrumentation of LLM providers and agent frameworks.

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