Neatlogs
Register when you ship Python or TypeScript LLM apps and need tracing, spans, prompt-template tracking, and auto-instrumentation for major SDKs via the neatlogs plugins.
Overview
neatlogs is a plugin marketplace for the Operate phase that adds Python and TypeScript neatlogs SDK instrumentation plugins for LLM tracing and agent observability in Claude Code.
What is this marketplace?
- 2 plugins: neatlogs-py and neatlogs-ts (MIT, v1.0.0 each)
- Python SDK: decorators, spans, prompt template tracking, auto-instrumentation
- Auto-instrumentation for OpenAI, Anthropic, LangChain, CrewAI, and related stacks (Python)
- TypeScript/Node SDK plugin for agent and LLM tracing in JS ecosystems
- Category observability with homepage neatlogs.com and GitHub repository neatlogs/skills
- Marketplace lists 2 plugins: neatlogs-py and neatlogs-ts, each v1.0.0 MIT
- Python plugin keywords include OpenAI, Anthropic, LangChain, and CrewAI auto-instrumentation
What problem does it solve?
LLM and agent apps fail opaquely—without spans and template-level tracing you cannot tell which step or prompt caused a bad production outcome.
Who is it for?
Indie builders running OpenAI, Anthropic, LangChain, or CrewAI style apps who want first-class LLM observability in code they control.
Skip if: Static sites or products with no LLM calls, or teams forbidden from adding third-party tracing SDKs.
What do I get? / Deliverables
Once registered, Claude can guide neatlogs SDK setup so your Python or TypeScript app emits traces and instrumentation hooks aligned to your stack.
- neatlogs-py and/or neatlogs-ts plugins available from the marketplace
- Instrumented code paths with spans, decorators, or auto-instrumentation hooks
- Clearer traceability for prompts and agent steps during debugging
Plugins in this marketplace
2 plugins — install individually after you add the marketplace.
Recommended Marketplaces
Journey fit
Observability for agents and LLM calls is a run-time concern—debugging production behavior and tracing failures—so Operate is the primary journey shelf. Monitoring matches LLM tracing, span visualization, and agent run diagnosis rather than initial integration coding alone.
How it compares
LLM observability SDK plugins, not a generic DevOps marketplace or a single UI review skill.
Common Questions / FAQ
Who is Neatlogs for?
Developers shipping Python or Node LLM/agent applications who want Claude-assisted setup of NeatLogs tracing and auto-instrumentation.
When should I use Neatlogs?
Use it when you are adding or hardening observability for production or staging LLM workflows, especially before debugging complex multi-step agents.
How do I add Neatlogs to my agent?
Add the Neatlogs/skills marketplace in Claude Code and enable Neatlogs-py and/or Neatlogs-ts depending on your language stack.