LLM Mart Basic

Investigate negative session feedback for a Whetstone skill when asked to diagnose its failures.

Evaluate Whetstone skills from session evidence when asked to compare procedure-following results or optimization candidates.

Revise and evaluate a Whetstone skill when asked to evolve or optimize that skill.

Prune stale Whetstone sync decision entries when asked to clean the sync log.

Run the Whetstone release workflow when explicitly asked to release this plugin.

Prepare or run Whetstone SkillOpt optimization when asked to optimize a process skill using SkillOpt.

Compare Whetstone with reference repositories when asked to sync cross-repository improvements.

Triage Whetstone pull requests when explicitly asked to group, label, and review open PRs.

Author a new Whetstone plugin skill when asked to write a skill without upstream skills.sh sources.

Fetches top-rated skills from skills.sh, analyzes them, and synthesizes one token-efficient skill combining the best elements. Use when the user asks to "distill skills for X", "find and combine skills for X", "synthesize skills", "merge skills", "make a skill for X from skills.s

Performs two-stage code reviews (spec compliance, then code quality) with severity-ranked findings. Use when asked to "review code", "review this PR", "check this diff", "review before merge", or mentions reviewing, auditing, or critiquing code changes, pull requests, or diffs.

Systematic root-cause debugging: reproduce, investigate, hypothesize, fix with verification. Use when asked to "debug this", "fix this bug", "why is this failing", "troubleshoot", or mentions errors, stack traces, broken tests, flaky tests, regressions, or unexpected behavior.

Defensive Bash scripting for Linux: safe foundations, argument parsing, production patterns, ShellCheck compliance. Use when writing "bash script", "shell script", "linux automation", "system script", "cron job", "deployment script", "CLI tool in bash", or "automate with bash".

Manages project documentation: AGENTS.md, README.md, and CONTRIBUTING.md. Use when asked to "update README", "update agents", "init agents", "create AGENTS.md", "update AGENTS.md", "update CONTRIBUTING", "update context files", or "init context". Not for general markdown editing.

Enhanced reasoning patterns via slash commands (/think, /verify, /adversarial, /edge, /compare, /confidence, /budget, /constrain, /json, /flip, /assumptions, /tensions, /analyze, /trade) or natural language ("argue against", "what could break", "show reasoning", "deep review", "m

Node.js backend patterns: framework selection, layered architecture, TypeScript, validation, error handling, security, production deployment. Use when building REST APIs, Express/Fastify servers, microservices, or server-side TypeScript.

Modern PHP 8.2+ and Laravel patterns: architecture, Eloquent, queues, Pest testing. Use when asked to "write PHP", "build a Laravel app", "fix Eloquent query", "add a queue job", "write a Pest test", or mentions PHP, Laravel, Eloquent, Blade, artisan, or migrations.

Pine Script v6 patterns: syntax rules, performance, debugging, backtesting, visualization. Use when asked to "write a Pine Script", "create an indicator", "build a strategy", "fix Pine code", or mentions PineScript, TradingView, indicator, strategy, or backtest.

Software implementation planning with file-based persistence (task_plan.md, findings.md, progress.md). Use when asked to "plan", "break down this feature", "implementation plan", or starting complex tasks needing >5 tool calls. Apply proactively before non-trivial coding.

PostgreSQL schema design, query optimization, indexing, and administration. Use when writing schemas, queries, migrations, or mentions PostgreSQL, Postgres, JSONB, partitioning, RLS, CTEs, window functions, EXPLAIN ANALYZE, or connection pooling.

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.

Inventory devices for an Auvik tenant with type, manage status, and lifecycle breakdown

Audit a tenant's networks, interfaces, and saved configurations; flag drift and missing backups

Single-tenant Auvik snapshot - devices, alerts, networks, billing usage

Phishing-simulation results and click-rate trend for a given window

Human risk score report for one client or the whole portfolio, built from training completion and phishing-simulation performance

Training completion snapshot for one client or the whole portfolio — completion rates, overdue users, and cadence status

Check backup health for one Axcient-protected device

Backup health overview across every device for one Axcient client

Azure cost and pricing analysis for a subscription — Advisor cost recommendations, retail pricing lookups, and quota-driven right-sizing signals, scoped to one subscription

Resource health and diagnostics triage for an Azure resource or subscription — Resource Health status, AppLens deep diagnostics, and Azure Monitor alert state

Portfolio-wide backup job health snapshot - failure count, at-risk clients, and storage trends

Restore-readiness check - has this actually been restore-tested, for one client or the whole portfolio

Retention and RPO compliance audit against contracted requirements, for one client or the whole portfolio

Create a new Better Stack uptime monitor

Triage current Better Stack incidents

Check all Better Stack monitor statuses and identify downtime

Search logs via Better Stack Logtail

Update a Better Stack status page with current status or maintenance

Investigate a single Blackpoint Cyber / CompassOne detection end-to-end

Portfolio-level Blackpoint Cyber / CompassOne rollup of detections and exposure across all tenants

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