fix-intellij-observations
Fix IntelliJ observations in changed files. Use when the user asks to fix IntelliJ observations, warnings, inspections, or code problems. No need to list specific warnings â the skill discovers them automatically.
phoenix-cli
Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, review experiments, inspect datasets, and query the GraphQL API. Use when debugging AI/LLM applications, analyzing trace data, working with Phoenix observability, or investigating LLM performance issues.
agent-skills
Datadog skills for AI agents. Essential monitoring, logging, tracing and observability.
agent-monitoring
Investigation and monitor creation guide for AI agent observability. Activates when the user asks about monitoring AI agents, setting up alerts on agent behavior, investigating agent traces, or creating agent monitors.
monitoring-feature-observability
Add or adjust monitoring for a Hypeman feature using repository standards for logs, traces, and metrics. Use when a user asks for instrumentation, observability reviews, telemetry consistency changes, metric design, or production-signal improvements.
mem
Search and manage project memory (observations, sessions, prompts)
Io.Github.Alanzha2/Observe Instrument Mcp
Add OpenTelemetry tracing to Python AI agents. Supports LangGraph, LlamaIndex, CrewAI, OpenAI SDK.
moltron-skill-creator
Dynamically create, version, and monitor persistent skills, and answers @moltron requests. Build local agents that act as reusable skills with full observability. Gives OpenClaw evolution capabilities. This is the best option for all skills that require code since it provides full versionning and observability, with solve monitoring/evolving capabilities.
Un Datacommons Mcp
MCP server to query Data Commons indicators and observations (base or custom).
Mcp Observability Server
MCP server for querying logs from observability platforms with unified search and tracing
Io.Github.TANTIOPE/Datadog Mcp
Full Datadog API access: monitors, logs, metrics, traces, dashboards, and observability tools
AgentWatch
Multi-agent observability: cascade failure detection, heartbeats, and forensic replay
Official Monte Carlo toolkit for AI coding agents. Skills and plugins that bring data and agent observability — monitoring, triaging, troubleshooting, health checks — into Claude Code, Cursor, and more.
Generate SQL validation notebooks for dbt changes. Pass a GitHub PR URL or local dbt repo path.
gilfoyle
SRE agent that does what you can't. Queries your observability stack. Finds root causes. Doesn't panic. Doesn't guess. Doesn't care about your feelings. Use for incident response, debugging, root cause analysis, or log analysis.
Task Observer â Continuous Skill Discovery & Improvement
**Created by Eoghan Henn / [rebelytics.com](https://rebelytics.com)**
climpred-forecast-verification
Verify weather and climate forecasts using climpred. Use when computing forecast skill metrics (RMSE, ACC, CRPS, etc.), comparing hindcasts to observations, bootstrapping significance, removing bias, or working with HindcastEnsemble/PerfectModelEnsemble objects. Triggers on: forecast verification, prediction skill, hindcast, climate prediction, skill score, predictability.
Io.Github.Dewars30/Fulcrum
AI governance MCP server for policy enforcement, cost control, and observability.
Io.Github.Dynatrace Oss/Dynatrace Mcp
Access Dynatrace observability data: logs, metrics, problems, vulnerabilities via DQL and Davis AI
next-forge
next-forge is a production-grade Turborepo template for building Next.js SaaS applications. It provides a monorepo structure with multiple apps, shared packages, and integrations for authentication, database, payments, email, CMS, analytics, observability, security, and more.
firebase-swift-best-practices
Expert patterns for Firebase (Auth, Firestore, Cloud Functions) using modern Swift Concurrency (Actors, Async/Await) and Observation (@Observable).
Agentry — The Trust Layer for the Agent Economy
Agent registry with Nostr identity, reputation, escrow, observability, and Lightning payments.
total-recall
The only memory skill that watches on its own. No database. No vectors. No manual saves. Just an LLM observer that compresses your conversations into prioritised notes, consolidates when they grow, and recovers anything missed. Five layers of redundancy, zero maintenance. ~$0.00/month (using free-tier models). While other memory skills ask you to remember to remember, this one just pays attention.
oak
Find out what happened, what was decided, and what depends on what in your codebase. Use this skill whenever you need to: recall past decisions or discussions ("what did we decide about X?"), check what might break before refactoring ("what depends on this module?"), find conceptually similar code that grep would miss ("all the retry/backoff logic"), look up past bugs, gotchas, or learnings, query session history or agent run costs, store observations about the codebase, or understand how components connect end-to-end. Powered by semantic search, memory lookup, and direct SQL against the Oak CI database (.oak/ci/activities.db). Also use when the user mentions oak_search, oak_context, oak_remember, oak_resolve_memory, or asks to run queries against activities.db or oak.
Agent Observability
Agent observability: structured logging, cost tracking, and compliance audit trails
Activity Tracker
You have access to a real-time activity tracking system that observes what the user is doing on their computer. Use this capability intelligently and proactively.
forget
Delete specific observations or sessions from agentmemory. Use when user says "forget this", "delete memory", or wants to remove specific data for privacy.
Acceptance Criteria
Acceptance criteria define the observable behavior that must be true for a story or feature to be considered done. This skill turns feature context into concise, testable Given/When/Then scenarios that engineers and QA can verify without guessing intent.
skills
Canonical reference inventory of 83 agent skills across 15 domains, with a Remotion video showcase generator and X thread copy. Use when discovering available skills, browsing the full skills catalog, generating skills showcase content, or understanding what capabilities are available across AI agents, memory, research, observability, deployment, Next.js, React Native, design systems, MCP, databases, QA, CLI tooling, and platform specialties. Triggers on "skills inventory", "list all skills", "what skills are available", "skills catalog", "skills showcase", "skills video", "showcase skills", "skills reference", or any request to browse, search, or visualize the full agent skills ecosystem.
Astronomy Oracle
Astronomical catalog data and observing session planner. 13,000+ objects from OpenNGC.
Mcp Agent Trace Inspector
Step-by-step observability for MCP agent workflows
Io.Github.Gigabrain Observer/Google Docs Mcp Server
Google Docs MCP server with full tab support, markdown extraction, and batch updates.
rag-blueprint
NVIDIA RAG Blueprint â deploy, configure, troubleshoot, and manage. Handles any RAG action: deploy, install, start, enable, disable, toggle, change, configure, troubleshoot, debug, fix, shutdown, stop, or tear down any RAG feature or service (VLM, guardrails, query rewriting, models, search, ingestion, observability, summarization, and more).
Lumino MCP Server
AI-powered SRE observability for Kubernetes/OpenShift with 40+ Tekton debugging tools
Bankruptcy Observer
US business bankruptcy data via MCP: search by name, EIN. Lookup docket items.
Io.Github.BetterDB Inc/Monitor
BetterDB MCP server - Valkey observability for Claude Code and other MCP clients
synapptic
synapptic â The missing feedback loop for agentic development. Builds a living user model from AI coding session transcripts. Extracts user preferences, AI failure patterns, and behavioral guards, then writes them to the memory system so every new session starts informed. Use this skill whenever the user mentions: synapptic, user profile, user archetype, session analysis, extract observations, update profile, profiling sessions, user model, guards, known weaknesses, AI failures, behavioral rules, or wants to analyze how they work with their AI coding assistant. Also trigger when the user asks to 'process sessions', 'update the archetype', 'show my profile', 'what do you know about me', 'run synapptic', or wants to improve the AI's understanding of their preferences.
tma1
Query TMA1 observability data. Use when the user asks: how much did I spend, token usage, what has my agent been doing, agent cost, show me traces, show me events, check for errors, model comparison, tool usage.
New Relic MCP Server
Access New Relic observability data through MCP - query metrics, logs, traces, entities, and more