raindrop-ai/workshop
Give your coding agent the power to write and run agent evals. observed · 2026-08-28
Health v2 · maintenance only
81/100
- Activity 99
- Release rhythm 99
- Longevity 8
Flags: young
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 0
- age_days: 125
- days_rel: 11
- days_push: 11
- n_releases_24m: 22
Adoption not part of the score
1058 stars · 63 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Raindrop Workshop is an open-source local debugger for AI agents that streams live traces of tokens, tool calls, and decisions into a browser UI. It integrates with coding agents like Claude Code to read traces, write and run evals against your codebase, and replay production traces locally.
Use cases
- debug my AI agent locally with live traces
- watch every token and tool call my LLM agent makes
- have Claude Code write and run agent evals
- replay a production agent trace against local code
- instrument my Vercel AI SDK or LangChain app for tracing
- turn agent failures into tests automatically
When to choose
- you're building LLM/agent apps and need local, real-time trace debugging
- you want your coding agent to autonomously write evals and fix agent failures
- you use supported SDKs (Vercel AI SDK, OpenAI/Anthropic SDKs, LangChain, CrewAI, Pydantic AI, Mastra) and want zero-config tracing
- you prefer a free, local, open-source tool over hosted-only observability
When to avoid
- you need production-scale observability and team dashboards - that's Raindrop Cloud, not Workshop
- your agent framework or SDK has no Raindrop integration
- you need a fully self-contained workflow with no cloud connection at all
- you're not working with LLM-powered agents or AI features
Facets
cli-tool · maturity active
tracing monitoring testing developer-tools mcp large-language-models developer-tools windows cli python go rust agent-debugging llm-observability agent-evals trace-replay coding-agent-integration local-debugger ai-agents debugging macos linux typescript
10 sources
- readme: https://github.com/raindrop-ai/workshop · fetched 2026-08-28 · 0bdb943a7293
- homepage: https://www.raindrop.ai/workshop/ · fetched 2026-08-29 · 32d2529f27e9
- site_page: https://www.raindrop.ai/docs/integrations/vercel-ai-sdk · fetched 2026-08-29 · 4d9fdce266de
- site_page: https://www.raindrop.ai/docs/integrations/openai-agents · fetched 2026-08-29 · a0ea9b863448
- site_page: https://www.raindrop.ai/docs/workshop/overview · fetched 2026-08-29 · 6e8188e03127
- site_page: https://www.raindrop.ai/docs/integrations/claude-agent-sdk · fetched 2026-08-29 · fad78bbcef89
- site_page: https://www.raindrop.ai/docs/integrations/langchain · fetched 2026-08-29 · 9123fb4c9709
- site_page: https://www.raindrop.ai/docs/integrations/crewai · fetched 2026-08-29 · 163e279eafd2
- site_page: https://www.raindrop.ai/docs/integrations/pydantic-ai · fetched 2026-08-29 · 64eaee9a4b29
- site_page: https://www.raindrop.ai/docs/integrations/mastra · fetched 2026-08-29 · b4101dc3f2c4
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| raindrop-ai/workshop | main | 81 |
For agents
markdown · JSON · MCP: product_card(name="raindrop-ai/workshop")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem