LLM Mart Basic

Design AWS non-destructive task automation using EventBridge, Step Functions, Lambda, Systems Manager Automation, SNS, SQS, approvals, notifications, reporting, and evidence gathering. Use only for read-only or coordination-safe automation; do not use for destructive remediation

Investigate broad AWS incidents and observability gaps using CloudWatch metrics, logs, alarms, traces, EventBridge events, service health, runbooks, timelines, blast radius, root-cause discipline, and post-incident actions. Prefer RDS/Aurora investigator for database-specific per

Repair AWS pipeline configuration, buildspecs, workflow files, deployment steps, artifact wiring, release guardrails, and CodeDeploy integration in-repo. Use for non-destructive CI/CD corrections; do not trigger live pipeline runs or mutate cloud state.

Use this skill when reviewing AWS ACM Private CA (Private Certificate Authority) issuer configurations for cert-manager. Trigger on any request to audit AWSPCAIssuer, AWSPCAClusterIssuer, IRSA policy for cert-manager, certificate template ARNs, CRL configuration, or cross-account

Investigate Amazon RDS and Aurora-specific incidents involving latency, connection exhaustion, slow queries, lock waits, storage pressure, CPU/I/O saturation, replica lag, failover behavior, Performance Insights, and database capacity. Prefer this for database performance; prefer

Review AWS resilience and business continuity strategy across RTO/RPO, dependency maps, multi-AZ, multi-Region, failover/failback, game days, runbooks, drift, and recovery validation. Prefer data protection backup steward for backup-plan/vault/restore implementation details.

Review Amazon S3 data perimeter and exposure posture across Block Public Access, Object Ownership, ACL removal, bucket/access point policies, TLS-only access, encryption, replication, lifecycle, logging, cross-account access, and prefix boundaries. Prefer this for S3 data exposur

Review broad AWS security posture across Security Hub CSPM, GuardDuty, Inspector, Macie, Config, CloudTrail, IAM, public exposure, vulnerability findings, and remediation governance. Prefer compliance evidence mapper for audit evidence packs, IAM skill for policy surgery, S3 peri

Review AWS Lambda-centered serverless workloads for production readiness across execution roles, event sources, retries, DLQs/destinations, concurrency, idempotency, observability, deployment safety, performance, cost, and rollback. Prefer event-driven architecture for EventBridg

Patch AWS serverless rollout definitions across Lambda, API Gateway, EventBridge, SQS, SNS, event source wiring, aliases, versions, and deployment config. Prefer this for repo-side rollout corrections; do not perform live rollout actions or destructive operations.

Design and stress-test AWS cross-domain solution architectures when the request spans multiple AWS domains or needs an architecture decision record. Prefer narrower AWS skills for single-domain IAM, network, EKS, ECS, serverless, RDS, DynamoDB, S3, Bedrock, IaC, cost, security, m

Triage AWS tickets and alerts using priority, owner, evidence, incident context, escalation path, OpsCenter, health signals, and safe next steps. Prefer this for non-destructive request coordination and escalation; prefer deep domain skills for implementation or root-cause invest

Review AWS workload cost posture against the Well-Architected Framework Cost Optimization Pillar. Covers cost visibility, tagging compliance, commitment coverage, rightsizing, Spot and managed service adoption, and idle resource identification. Use when auditing cloud spend, plan

Review AWS workload reliability posture against the Well-Architected Framework Reliability Pillar. Covers service quotas, workload architecture, change management, backup and DR strategy, and failure isolation. Use when auditing availability design, planning disaster recovery, or

Review AWS workloads against the Well-Architected Framework Security Pillar: identity foundations, detective controls, infrastructure protection, data protection, and incident response readiness.

Use this skill for Microsoft Foundry and Azure AI Foundry operations governance: resource-versus-project boundary design, RBAC review, quota planning, network isolation, logging, and safe MCP-backed read or write execution. Trigger when the user asks how to run Foundry safely acr

Operate Azure Kubernetes Service with an adversarial production posture. Use for AKS architecture sanity checks, upgrade safety, node-pool strategy, workload identity, network policy, scaling, observability, and operator-readiness reviews.

Review Azure App Service and Web Apps for production readiness across plan tier fit, slots, networking, private ingress, identities, secrets, scaling, diagnostics, resilience, backup, rollback, and operator readiness. Use when a team wants a real go/no-go decision instead of shal

Use this skill for Azure Cosmos DB application development work, especially NoSQL data modeling, document structure, partition-aware access patterns, point reads, query design, SDK usage, transactional batch scope, consistency-aware reads, change feed integration, and Cosmos DB d

Use this skill for Azure Cosmos DB performance investigation, especially RU spikes, query latency, throttling, hot partitions, indexing inefficiency, partition-skew analysis, request-charge profiling, diagnostic-log review, and evidence-driven remediation planning.

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.

Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

The fastest way to put Volcengine Ark in your terminal and your AI agent — go from prompt to generated media, multimodal answer, or deployed endpoint in a sin…

本地私有、开源的自进化跨平台 AI 内容发现 Agent：先理解你，再主动从 B站、小红书、抖音、YouTube、X、知乎、Reddit、微博等平台与开放 Web 寻找内容。（支持 deepseek harness 插件） | Local-first open-source cross-platform AI cont…

Persistent memory for AI coding agents — one verified kb_search replaces the grep/find/ls orientation loop. Cross-repo, CPU-only, zero token spend.

AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Co…

The batteries-included, No-Code FinOps automation platform, with the AI you trust.

Open-source 3D AI agent framework — GLB/glTF avatars with LLM brains, memory, emotions, and autonomous payments. MCP server · x402 · Solana/EVM · Three.js. Embe…

XLSX parser for LLMs, RAG, LangChain, LangGraph, CrewAI, Claude, MCP — turns Excel (.xlsx) into citation-ready JSON with formulas, charts, dependency graphs, an…

Hermes-Relay — Your Hermes AI agent, in your pocket — chat, voice, and control.

A minimalist, terminal-native coding agent written in C.

AI-powered OSINT agent with interactive REPL, MCP server, and CLI. 19 tools. Works with Claude, GPT-4, or local models. For authorized security research only.

AI pair programming in your terminal — one static binary, sub-ms startup, any model

Where data access meets operational intelligence

Build your own security agents. Open-source framework for agents with live, read-only access to your infrastructure, with no path to widen it. Reasons across AW…

Multi-workspace terminal aggregator with Claude Code AI integration

Go implementation of AI coding agent

Harness engineering beginner tutorial, from 0 to 1

Generate images directly in DeepSeek Harness chats

A smarter, self-hosted AI assistant — multi-user, multi-agent.

Turn any research paper into a commercialization report — 6 AI agents, TRL/MRL scoring, patent landscape, market intelligence, verified citations. DeepSeek / Op…

Power BI CLI - semantic models (.NET TOM) and PBIR reports for token-efficient AI agent usage, built for Claude Code