phoenix-observability

21.8k

davila7

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

langfuse

21.8k

davila7

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

kaizen:root-cause-tracing

563

NeoLabHQ

Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior

tracing-upstream-lineage

258

astronomer

Trace upstream data lineage. Use when the user asks where data comes from, what feeds a table, upstream dependencies, data sources, or needs to understand data origins.

root-cause-tracing

201

elianiva

Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior

debugging-systematic

95

korallis

Apply systematic root cause analysis and debugging methodologies to diagnose and fix bugs, test failures, and unexpected behavior. Use when encountering production issues, investigating test failures, diagnosing performance problems, tracing error sources through call stacks, analyzing logs and stack traces, reproducing inconsistent bugs, debugging race conditions, investigating memory leaks, or applying scientific method to problem-solving before proposing fixes.

root-cause-tracing

95

korallis

Trace bugs backward through call stacks and execution flows to identify the original source of errors, invalid data, or incorrect behavior. Use when debugging complex issues, tracing error origins, investigating data corruption, following execution paths, identifying where invalid data enters the system, or finding root causes of cascading failures.

build-pov-ray

62

letta-ai

Guidance for compiling POV-Ray 2.2 (a 1990s-era ray tracing software) from source on modern Linux systems. This skill should be used when the task involves downloading, extracting, and building POV-Ray 2.2 or similar legacy/historical software that requires special handling for modern compiler compatibility.

path-tracing-reverse

62

letta-ai

This skill provides guidance for reverse engineering compiled binaries to produce equivalent source code. It applies when tasks require analyzing executables, extracting algorithms and constants, and recreating identical program behavior in source form. Use when the goal is byte-for-byte or pixel-perfect reproduction of binary output.

root-cause-tracing

52

dsifry

Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior

source-tracing

21

hacket

Trace back from high-entropy secondary content to low-entropy, authoritative, original information sources. This skill uses a structured process to help users verify the authenticity of messages, understand the original context, and build independent information judgment and source-tracing abilities.

Sentry Skill

20

julianobarbosa

Comprehensive skill for Sentry error monitoring and performance tracking. Use when Claude needs to (1) configure Sentry SDKs for error tracking and performance monitoring, (2) manage releases, source maps, and debug symbols via CLI, (3) query issues, events, and metrics via API, (4) set up alerting and notification rules, (5) configure sampling strategies and quota management, (6) deploy self-hosted Sentry instances, (7) integrate with OpenTelemetry for distributed tracing, or perform any other Sentry automation task.

root-cause-tracing

14

CatsMiaow

Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior

Root Cause Tracing

12

hamr0

Use when errors occur deep in execution and you need to trace back to find the original trigger — systematically traces bugs backward through the call stack, adding instrumentation when needed to identify the source of invalid data or incorrect behavior.

langfuse

5

agent-skills-hub

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

langfuse

4

ngxtm

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debug...

root-cause-tracing

4

alexsandrocruz

Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior

Hallucination Detector

4

kingdon

Detect potential hallucinations by tracing claims back to source materials and validating whether fetched information was actually used to support conclusions. Trigger with /hallucination-check

reverse-engineering-ios-app-with-frida

2

mukul975

Reverse engineers iOS applications using Frida dynamic instrumentation to understand internal logic, extract encryption keys, bypass security controls, and discover hidden functionality without source code access. Use when performing authorized iOS penetration testing, analyzing proprietary protocols, understanding obfuscated logic, or extracting runtime secrets from iOS binaries. Activates for requests involving iOS reverse engineering, Frida iOS hooking, Objective-C/Swift method tracing, or iOS binary analysis.

flow-analysis

2

lewing

Analyze VMR codeflow health using maestro MCP tools and GitHub MCP tools. USE FOR: investigating stale codeflow PRs, checking if fixes have flowed through the VMR pipeline, debugging dependency update issues, checking overall flow status for a repo, diagnosing why backflow PRs are missing or blocked, subscription health, build freshness, URLs containing dotnet-maestro or "Source code updates from dotnet/dotnet". DO NOT USE FOR: CI build failures (use ci-analysis skill), code review (use code-review skill), general PR investigation without codeflow context, tracing whether a specific commit/PR has reached another repo (use flow-tracing skill). INVOKES: maestro and GitHub MCP tools, flow-health.cs script.

langfuse

1

rootcastleco

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debug...

security-scan

1

phrazzld

Whole-codebase vulnerability analysis leveraging a 1M-token context window. Loads the entire project source and runs deep security analysis in a single pass. OWASP Top 10, cross-module data-flow tracing, dependency audit, secrets scan.

agent-qa

bmartinezg

Autonomous QA agent that performs deep code quality inspection in three phases. Phase 1: Full codebase analysis — maps architecture, stack, modules, dependencies, and generates a structured test-case document with every functionality and verification checkpoint organized by module. Phase 2: Code tracing and verification — traces each functionality end-to-end through the source code, verifying integrations, data flow, naming conventions, formatting, logic correctness, and edge cases. Produces a detailed report with pass/fail results per checkpoint. Phase 3: Fix iteration — presents all findings to the user for confirmation, then iterates through approved issues applying fixes directly in the codebase. Use when the user says "agent qa", "QA", "quality assurance", "quality inspection", "code audit", "code scan", "deep code review", "trace code", "verify code", "scan project", "quality check", "code quality", "audit code", "inspect code", or "run QA".

langfuse

oki3505F

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

agent-qa

bmartinezg

Autonomous QA agent that performs deep code quality inspection in three phases. Phase 1: Full codebase analysis — maps architecture, stack, modules, dependencies, and generates a structured test-case document with every functionality and verification checkpoint organized by module. Phase 2: Code tracing and verification — traces each functionality end-to-end through the source code, verifying integrations, data flow, naming conventions, formatting, logic correctness, and edge cases. Produces a detailed report with pass/fail results per checkpoint. Phase 3: Fix iteration — presents all findings to the user for confirmation, then iterates through approved issues applying fixes directly in the codebase. Use when the user says "agent qa", "QA", "quality assurance", "quality inspection", "code audit", "code scan", "deep code review", "trace code", "verify code", "scan project", "quality check", "code quality", "audit code", "inspect code", or "run QA".

langfuse

haniakrim21

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

tauri-devtools

yigitkonur

CrabNebula DevTools integration for Tauri v2 apps. Gives AI agents visibility into the Rust side — console logs with tracing spans, IPC call timings, live config inspection, and frontend source browsing. Use when debugging Tauri apps or when browser devtools isn't enough.

observability

littlebearapps

Observability standards including logging, tracing, sampling profiles, source maps, and audit scoring rubric. Load when configuring observability or improving audit scores.

Langfuse

reikiplanet

Expert in Langfuse — the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integrations with LangChain, LlamaIndex, and OpenAI. Essential for debugging and monitoring LLM-based applications.