LLM Mart Basic

Use when a C++ project adopts C++20 modules: named modules, partitions, header units, the global module fragment, CMake CXX_MODULES, or a BMI lookup error. Not for flag basics: use clang.

Use when a C++ template error needs decoding, a template needs a concept or requires-clause instead of SFINAE, or template instantiation is slowing compilation. Not for C++20 modules: use cpp-modules.

Use when diagnosing cache misses with perf, fixing false sharing, choosing AoS or SoA layout, or adding software prefetch. Not for cache theory: use memory-hierarchy-and-caches.

Use when writing, optimizing, or benchmarking a C++ CPU kernel with AVX2 or AVX512 intrinsics for the Hugging Face kernels ecosystem. Not for CUDA kernels: use cuda.

Use when explaining pipeline stages, data or control hazards, forwarding, stalls, or superscalar basics behind a counter reading. Not for mispredict cost: use branch-prediction-and-speculation.

Use when the user asks to create a new branch or start work on one. Not for remote, credential, publish, deploy, or irreversible changes.

Use when asked to create a multi-session learning plan. Returns a milestoned plan, practice, and review rubric. Don't use for tasks that require source or remote-system changes.

Use when asked to create a local agent-plugin directory tree or marketplace package. Not for remote, credential, publish, deploy, or irreversible changes.

Use when asked to create or update a PR, revise its description, or link issue references to its body. Not for multi-PR stacks: use gate-and-merge. Not for releases: use git-workflow-and-versioning.

Use when independent proposals on a contested decision need cross-critique before choosing, reusing the original authors. Not for parallel multi-stance investigation: use council.

Use when compiling for ARM, AArch64, RISC-V, or MIPS from x86-64 with a GCC cross toolchain: triplets, sysroots, pkg-config, CMake toolchain files, QEMU. Not for Zig: use zig-cross.

Use when one reviewer is not enough because failure modes are heterogeneous, or a claim needs cross-lens pressure before it ships. Not for collapsing a decision field: use converge.

Use when a long agentic project needs each cycle to end in a learning memo and a keep/iterate/restart decision. Not for single-pass builds.

Use when asked for a sequence diagram of cryptographic protocol semantics from code, prose, RFCs, papers, ProVerif, or Tamarin, or for code/spec divergence. Not for architecture: use diagramming-code.

Use when writing CUDA kernels, managing the thread, block, and grid hierarchy, tiling shared memory, using streams, setting nvcc flags, or using Thrust. Not for kernel debugging: use cuda-debugging.

Use when debugging CUDA with cuda-gdb or Compute Sanitizer, reading GPU core dumps, using device printf, or triaging error codes 700, 701, 702, and 719. Not for performance: use cuda-profiling.

Use when profiling CUDA with Nsight Systems or Nsight Compute, reading roofline and occupancy metrics, or annotating phases with NVTX. Not for correctness: use cuda-debugging.

Use when Survey and Job Culture Index profiles need analysis for stress, burnout, disengagement, or flight-risk signals. Not for clinical diagnosis: use a qualified clinician.

Use when two colleagues' working friction needs trait-based explanation, accommodations, process changes, and escalation boundaries, or for manager-report friction. Not for performance adjudication.

Use when a Culture Index profile needs comparison with role requirements, team composition, and manager profile for hiring. Not for transcript prediction: use culture-interview-profile-prediction.

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.

One-screen inventory of skills, agents, commands, MCP servers, and hooks counts.

List the file-based memory store grouped by project (auto-memory) plus the CLAUDE.md files.

Show current Claude Code spend versus a budget number

Quick month-end spend projection from the daily trend

List the most expensive sessions pushing your spend up

Print the Agent Monitor dashboard URL and how to start/open it

Check Agent Monitor reachability and print UP/DOWN with latency

One-line Agent Monitor health + counts summary from /api/stats

Quick connectivity + health probe of the Agent Monitor dashboard.

Export Agent Monitor data (sessions/events/analytics/costs/all) as json/csv/md.

Show the latest N ingested events with timestamp, event_type, and tool_name.

List current cost and token outlier sessions via z-score

Compare two sessions side-by-side with cost and workflow deltas

Surface the top 3 data-backed insights about your Claude Code usage right now

Read-only inventory of CCAM alerts, webhook targets, and remote sources

CCAM platform status across hooks, config, updates, and MCP prerequisites

One-screen focus snapshot — avg turn duration, thinking-block usage, and longest sessions.

Quick daily standup from today's Claude Code sessions — grouped by project, with cost and errors.

Suggest the next action from your most recent in-progress sessions and recent errors.

List the most recent APIError events with their session and a summary

Open‑WebUI Tools is a modular toolkit designed to extend and enrich your Open WebUI instance, turning it into a powerful AI workstation. With a suite of over 15…

The token-efficient agentic coding workbench. Built for a future where every token counts — it optimizes token usage at the agent-loop level, saving 70%+ on lon…

MCP server for controlling a real iPhone via macOS iPhone Mirroring...and any MacOs app. Screenshot, tap, swipe, type — from any MCP client.

One desktop for all your AI coding Agent — Claude Code, Codex CLI & Gemini CLI. Auto-detect, one-click install, unified chat, file explorer, terminal & editor.…

Pi — A cross-platform AI coding agent, bringing the Claude Code experience to your desktop. No environment setup, no terminal commands. Download and start codin…

DeepSeek Harness Desktop (dsh-desktop). EAC: Embracing All Creation (揽尽万象). Bundled Node.js runtime with full dsh-CLI kernel, one-click startup, 10 built-in UI…

A telegram bot for searching and auto-saving.

金蝶云星空 K3Cloud MCP Server，让 AI 助手（Claude Desktop、Claude Code、Cursor、Cline、Cherry Studio、Openclaw 等任意支持 MCP 协议的客户端）通过自然语言查询和操作金蝶 ERP 系统。

Rewrite frontier research using allegorical structural mapping.

Free4Chat is a temporary collaboration fabric for Humans and Agents.

Give any AI agent a full desktop — it sees the screen, clicks, types, and runs apps like a human. Automate anything with a UI: browsers, legacy software, intern…

A personal AI agent that can work safely on your machine, remember useful context, and keep its data under your control.

A framework for AI-driven economic activity. Declarative, composable, observable, deterministic.

Open-source, self-hosted customer support desk in a single binary. A lightweight alternative to Intercom, Zendesk, Chatwoot.

54 rigorous skills for Codex, OpenCode, and Pi: code review, security audit, feature development, frontend design, MCP tools, Hugging Face ML/training, and more…

A wonderful list of Game Development resources.

Open Science Desktop — local-first, model-agnostic AI research workbench for macOS, Windows & Linux. Open-source Claude Science desktop alternative built on Tau…

Lexora — Personal AI workspace built around Desktop / 以 Desktop 为核心的个人 AI 工作台

Open-source, AI-native Evernote alternative with native MCP. Zero-cost on Cloudflare or self-hosted with Docker.

Full job-hunt Claude skill bundle — Job Description decoder + Resume builder (11 templates) + Behavioral Interview / story bank. Three self-contained sub-skills…