LLM Mart Basic

Use this skill when you need to design automation testing approaches using patterns like POM, data-driven testing, or BDD; triggers include automation testing and test automation strategy.

Use this skill when you need to select boundary and near-boundary candidates from sourced value, length, time, and resource constraints; triggers include 边界值分析 and boundary value test design.

Use this skill when you need to write clear, reproducible bug reports with steps, environment details, and evidence; triggers include bug reporting and defect reporting.

Use this skill when requirements, policies, contracts, or workflows need traceable business rules extracted before design or testing; triggers include business rule extraction, policy rule inventory, and atomic rule analysis.

Use this skill when you need to assess capacity demand, headroom, constraints, and planning assumptions; triggers include capacity planning analysis.

Use this skill when you need to analyze how a code, configuration, or requirement change affects quality scope; triggers include change impact analysis.

Use this skill when you need evidence-bounded chaos-testing analysis and validation preparation; triggers include 混沌测试 and chaos-testing.

Use this skill when you need evidence-bounded pipeline stages, feedback latency, resources, flakiness, caching/sharding, and rollback boundaries; triggers include CI 测试流水线 and CI test pipeline.

Use this skill when you need evidence-bounded circuit-breaker-testing analysis and validation preparation; triggers include 熔断器测试 and circuit-breaker-testing.

Use this skill when you need a risk-driven code review of a PR/diff with severity-ranked findings and actionable fixes; triggers include code review, PR review,.

Use this skill when you need to select high-risk multi-factor combinations after factors, values, and constraints are explicit; triggers include 组合测试 and combinatorial test design.

Use this skill when you need to select evidence-backed browser, engine, device, and version coverage; triggers include 跨浏览器测试 and cross-browser testing.

Use this skill when an ERD, DDL, ORM schema, or migration plan needs an evidence-bounded database design review before implementation; triggers include database design review, migration readiness review, and schema quality audit.

Use this skill when you need to turn conditions, rules, actions, and outcomes into an auditable set of rule combinations; triggers include 决策表测试设计 and decision table test design.

Use this skill when you need evidence-bounded dependency-failure-testing analysis and validation preparation; triggers include 依赖故障测试 and dependency-failure-testing.

Use this skill when you need evidence-bounded disaster-recovery-testing analysis and validation preparation; triggers include 灾备测试 and disaster-recovery-testing.

Use this skill when you need to analyze distributed traces for call paths, latency, errors, and evidence gaps; triggers include distributed trace analysis.

Use this skill when you need to discover boundary, rare, limit, ordering, or combination scenarios from product and test evidence; triggers include edge case discovery.

Use this skill when you need to partition inputs into evidence-backed valid, invalid, and unknown classes based on constraints, rules, and response differences; triggers include 等价类划分 and equivalence partitioning test design.

Use this skill when error taxonomy, retries, timeouts, fallback, or recovery design needs an evidence-bounded review before implementation; triggers include error handling design review, failure-path review, and recovery readiness review.

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.

Improve an existing agent through performance baselines, prompt engineering, A/B testing, and staged rollout

Optimize multi-agent system performance through profiling, context window tuning, coordination efficiency, and cost and latency tradeoffs

Debug issues using competing hypotheses with parallel investigation by multiple agents

Task delegation dashboard for managing team workload, assignments, and rebalancing

Develop features in parallel with multiple agents using file ownership boundaries and dependency management

Launch a multi-reviewer parallel code review with specialized review dimensions

Gracefully shut down an agent team, collect final results, and clean up resources

Spawn an agent team using presets (review, debug, feature, fullstack, research, security, migration) or custom composition

Display team members, task status, and progress for an active agent team

Build realistic API mock servers with request stubbing, dynamic data, test scenarios, and contract testing

Orchestrate end-to-end application performance optimization from profiling to monitoring

Orchestrate end-to-end feature development from requirements to deployment

Set up PreToolUse hook to block --no-verify and other git bypass flags in Claude Code projects

Generate comprehensive C4 architecture documentation (Context, Container, Component, Code) for a codebase using bottom-up analysis and four coordinated C4 agents.

Automate CI/CD pipelines, releases, and development workflows with GitHub Actions, pre-commit hooks, and infrastructure automation

Explain complex code, algorithms, and design patterns with step-by-step breakdowns, visual diagrams, and interactive examples

Generate API, architecture, code, and user documentation from a codebase and automate keeping it current

Restore saved project context and decisions to resume a session

Refactor provided code for cleanliness, maintainability, and alignment with SOLID principles and modern best practices — no over-engineering.

Analyze and remediate technical debt — inventory debt items, score by impact, and produce a prioritized remediation plan with estimated effort.

AI coding platform for teams

AI Multi-Agent Framework in .NET

Production-ready code examples for Telnyx AI Communications Infrastructure — Voice AI, SMS, SIP, and IoT APIs

UltraGameStudio - AI coding agent for game development: engine workflows, gameplay code, and asset generation.

🦞 ResearchClawBench: Evaluating AI Agents for Automated Research from Re-Discovery to New-Discovery

The context-aware model router that learns & adapts to your long-horizon coding agent workflows. Lightweight & extensible, works with any harnesses, any models,…

Open-source sandboxes where coding agents build and deploy. Spin up isolated environments where Claude Code, Cursor, and other agents code and deploy software.

Native desktop UI for Claude Code with orchestration, streaming, background agents, and multi-provider support. Built with Tauri + React.

OpenCode mobile client via Telegram: run and monitor AI coding tasks from your phone while everything runs locally on your machine. Scheduled tasks support.

Terminal session manager for AI coding agents. One TUI for Claude, Gemini, OpenCode, Codex, and more.

Exposes internet search tools for use by LLM-backed Assist in Home Assistant

Templates and workflow for generating PRDs, Tech Designs, and MVP and more using LLMs for AI IDEs

Versus Incident is the self-hosted AI SRE agent. It learns what your system normally look like and escalates only what is new or unexpected issues — routing to…

Browser-native side panel for Hermes Agent — connect web context to your local Hermes runtime.

Agentic-friendly CLI generator for APIs: turn Swagger, OpenAPI, and google.api.http protos into single-binary CLIs with catalogs and generated Skills.

Open-source agent platform for Global × China enterprises — wire every system through one agent core. Self-hosted, any LLM.

Official python implementation of UTCP. UTCP is an open standard that lets AI agents call any API directly, without extra middleware.

An agent small enough to run anywhere. A minimal agentic runtime in C — ~380 lines, 54KB binary, ~2MB RAM. A skill file + an LLM + a shell loop, no framework.

AgentiLoop Agent! An Autonomous Agentic Agent for Mac, and exclusive Apple only harnesss. Suppprtd automation, scripting, coding, build anything and more. Power…

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