claude

neatlogs-py

Instrument Python LLM applications with the neatlogs SDK — tracing, semantic spans, supported wrappers and framework integrations for OpenAI, Anthropic, LangChain, CrewAI, and more.

0 on GitHubby NeatLogsv1.2.13MITupdated 7 days agoobservability
/

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

What it installs

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.

View source on GitHub neatlogs.com

More from neatlogs/skills

All 5 plugins →

Instrument Go LLM applications with the neatlogs SDK — Gemini via WrapGenAI, Google ADK via the private-provider integration, explicit span helpers, custom boundaries, and per-request identity.

23 skills

0

Send traces to Neatlogs from unsupported languages with dependency-free HTTP ingest at POST /v1/trace, or configure OTLP/gRPC for existing OpenTelemetry applications and Collectors.

23 skills

0

Use the NeatLogs Public API and neatlogs-cli to read project-scoped traces and other supported cloud resources safely.

23 skills

0

Instrument TypeScript/Node.js LLM applications with the neatlogs SDK — semantic spans, supported wrappers and framework integrations for OpenAI, Anthropic, LangChain, Mastra, Vercel AI SDK, and more.

23 skills

0

Similar plugins

Claude API and SDK documentation skill for building LLM-powered applications

19 skills

anthropics/skills 193,780

Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.

2 skills · 2 commands · 2 agents · 1 MCP server

f/prompts.chat 177,027

Security review for Claude-generated code. Pattern-based warnings on edits, LLM-powered diff review on Stop, and an agentic commit reviewer that catches injection, XSS, SSRF, hardcoded secrets, and 25+ other vulnerability classes.

hooks

anthropics/claude-code 155,476

CMEM Pro

claude

CMEM Pro for the Claude app - hooks stream tool use to cmem.ai and inject observations into new sessions and agents

3 skills · 1 MCP server · hooks

thedotmack/claude-mem 116,618

RuVLLM local inference with chat formatting, MicroLoRA fine-tuning, and SONA adaptation

3 skills · 1 command · 1 agent

ruvnet/ruflo 81,589

Skill: add headroom-ai compress() to a Python or TypeScript app to cut LLM input tokens (tool outputs, logs, JSON, chat history). No API key.

1 skill

headroomlabs-ai/headroom 79,508

Maintain neatlogs-py?

This page updates itself from your repo. Add the badge to your README, or get it Featured to pin it above the organic results with a followed link to your site.

claude & codex plugins5 plugins