LLM Mart Basic

Automates incident response for AWS CloudWatch alarms using boto3, the CloudWatch GetMetricData API, and AWS Systems Manager runbook documents. Maps alarm states to diagnostic procedures and remediation actions.

Triages AWS CloudWatch alarms using boto3 CloudWatch.describe_alarms, CloudWatch Logs Insights queries, and AWS X-Ray trace analysis via the xray-sdk. Correlates alarm triggers with deployment events.

Triages AWS CloudWatch alarms using the CloudWatch DescribeAlarms API, GetMetricData for historical analysis, and CloudTrail LookupEvents for root cause correlation. Prioritizes alerts by blast radius and provides remediation playbooks.

Triages AWS CloudWatch alarms by correlating alarm state changes with CloudTrail events and EC2 instance health using boto3. Classifies alarms by severity, identifies root cause candidates, and updates OpsGenie alerts.

Uses AWS CloudWatch SDK (boto3) to configure anomaly detection bands on metrics via PutAnomalyDetector API. Integrates with SNS for notifications and CloudWatch Synthetics for canary-based uptime monitoring.

Investigates CloudWatch metric anomalies using the AWS SDK CloudWatch.getMetricData and Logs.filterLogEvents APIs. Correlates metric spikes with log patterns and deployment events from CodeDeploy.

Executes structured diagnostic runbooks when CloudWatch Anomaly Detection triggers alarms. Uses the AWS SDK CloudWatch client (GetMetricData, DescribeAlarms) to gather context and suggest remediations.

Creates and manages AWS CloudWatch composite alarms using the CloudWatch PutCompositeAlarm API. Builds alarm rule expressions from existing metric alarms with AND/OR/NOT logic for multi-signal alerting.

Runs CloudWatch Logs Insights queries via AWS SDK for JavaScript v3. Analyzes Lambda cold starts, API Gateway latency, and ECS container logs. Generates anomaly detection alarms with math expressions.

Builds CloudWatch Logs Insights queries and metric alarms using AWS SDK v3 (@aws-sdk/client-cloudwatch-logs, @aws-sdk/client-cloudwatch). Generates cross-account observability dashboards with CloudWatch Metrics Insights.

Analyzes AWS CloudWatch Logs using the CloudWatch Logs API and Logs Insights query syntax. Identifies error patterns, calculates error rates, and generates metric filters from log data.

Investigates anomalous patterns in AWS CloudWatch Logs using the CloudWatch Logs Insights API and CloudWatch Anomaly Detection. Correlates log spikes with deployment events via AWS CodeDeploy API.

Scans AWS CloudWatch Logs using the CloudWatch Logs Insights API and CloudWatch Anomaly Detection API. Identifies unusual error patterns, latency spikes, and log volume anomalies across log groups.

Uses AWS SDK CloudWatchClient GetMetricData and CloudWatch Logs Insights StartQueryExecution to automate incident triage. Correlates alarms via DescribeAlarms with X-Ray trace segments for root cause analysis.

Manages AWS CodePipeline stages and actions using AWS SDK for JavaScript (CodePipeline, CodeBuild, CodeDeploy APIs). Automates blue-green deployments and cross-account pipeline configurations.

Uses boto3 and the AWS IAM Access Analyzer API to enumerate all roles, policies, and users, then flags permission combinations that could allow privilege escalation to AdministratorAccess. Outputs findings mapped to MITRE ATT&CK TA0004 with remediation steps and least-privilege r

Imported from agentskillexchange/skills/skills/aws-lambda-mcp-server.

The official AWS Labs MCP server collection provides AI agents with structured access to AWS documentation, service APIs, billing data, and infrastructure metadata through the Model Context Protocol, built and maintained by AWS for secure cloud automation workflows.

Imported from agentskillexchange/skills/skills/aws-s3-mcp-server.

Orchestrates AWS data pipelines using @aws-sdk/client-s3 and @aws-sdk/client-sqs. Manages S3 object lifecycle with PutObjectCommand/GetObjectCommand, processes SQS message queues via ReceiveMessageCommand with long polling, and configures S3 event notifications to SQS for event-d

Fourteen posts of being wrong in production, compressed to checkboxes

Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.

A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.

A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.

None of the safety came from the model. It came from six boring habits.

Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.

Six hours in, one step left, everything green, and the incident that didn't happen

CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.

Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it

An API request routing a model's tool call through an approval gate to a remote MCP server

31 config keys, two audits, and why the first one was wrong in both directions

The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.

Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.

Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.

"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks

stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.

The most important rule wasn't about what I could change. It was about what I was allowed to display.

Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.

`crabbox inspect` prints the full record for a single lease: state, provider,

Run named, repo-local jobs defined in your Crabbox config.

`crabbox list` shows the current Crabbox machines (leases) for a provider. It is

`crabbox login` authenticates the CLI against a coordinator, stores the

`crabbox logout` clears the stored broker token from your user config so the CLI

`crabbox logs` prints the retained command output for a recorded run.

`crabbox marketplace` previews the Crabbox credits gateway: one Crabbox billing

`crabbox media` turns a recorded desktop video into lightweight review

`crabbox open` prepares an existing SSH-capable lease for an external editor.

`crabbox pause` pauses a single lease, freeing the remote compute while

`crabbox pond` is the cross-provider peer-discovery and lifecycle surface for a

`crabbox pool` contains machine-pool helpers. `pool list` keeps the older

`crabbox ports` bridges provider-native port publishing for an existing Crabbox

`crabbox prewarm` leases a reusable box and prepares it for test runs. For

`crabbox providers` prints the provider capability matrix that the CLI compiles

`crabbox receipt <run-id>` retrieves a brokered run's committed terminal

`crabbox results` prints the structured test summary attached to a recorded

`crabbox resume` resumes a lease previously paused with [`pause`](pause.md),

`crabbox run` syncs the current dirty checkout to a box, runs a command there,

`crabbox screenshot` captures a single PNG from a desktop lease without opening a

Build AI Agents like playing LEGOs. Everything is a Plugin.

The coding agent that answers to you, your model, your machine, your rules.

CI-native agent CLI tool for deterministic pipeline gating.

Local-first cross-platform desktop workspace for Claude Code / agents: multi-agent, Git worktrees, code diffs, skill marketplace, multi-model, Computer Use, tas…

Local-first visual generation runtime and studio for people and coding agents, with reproducible image and video workflows across multiple providers.

A token-efficient MCP server for safe, line-oriented text file editing with partial reads, hash-based conflict detection, and atomic multi-file operations.

Open-source, evidence-driven MCP server for RTL simulation debugging: correlate VCS/Xcelium logs, VCD/FSDB waveforms, SystemVerilog/UVM source, hierarchy, and c…

runs anywhere. uses anything

One macOS app for Claude Code, Codex, and every agent runtime you use — scheduled runs, global hotkey launcher, per-run git worktrees, one review board.

Soul-driven AI agent with permission-hardened tools, token budgets, and multi-channel access. Runs 24/7 from CLI or Telegram.

Email, SMS & phone-call infrastructure for AI agents — send and receive real email and text messages, and place agent-driven outbound voice calls, all programma…

55 MCP tools to drive the Unity Editor from any MCP-compatible AI agent — scenes, GameObjects, prefabs, assets, tests, and builds. OpenClaw gateway included for…

Google Ads MCP + Meta Ads MCP + GA4 in one server for Claude, ChatGPT, Cursor & n8n — 250+ tools, hosted remote MCP, OAuth login, no API keys. By Ryze AI.

Claude Code & Codex 本地 token 追踪 — 状态栏（Codex 业界首创伪 statusline）、GitHub 风格热力图、多模型成本分析。 | Local token tracker for Claude Code & Codex — status line (industry-first…

Empower the Shell to think. Evolve Operations.

🤖 A full-stack Agent Chat Runtime for pre-production validation, built with act, TypeScript, and LangGraph JS combining streaming, multimodal, HITL, and tools…

Cerul — video memory infrastructure for AI products. SDKs, CLI, MCP, and developer integrations.

Stealth headless browser for AI agents — bypass Cloudflare, bot detection, and anti-scraping. Drop-in Puppeteer/Playwright replacement.

Web research for your agents with smart and safe tooling + knowledge store

FuXi is a fast, self-contained AI coding agent that lives in your terminal — edit code, run commands, and drive tools, with cost-aware routing across LLM provid…