LLM Mart Basic

Use when reducing C/C++ compilation times with ccache, sccache, distcc, unity builds, precompiled headers, split DWARF, IWYU, or link time reduction.

Use when asked to analyze a Burp Suite .burp project for audit items, request/response metadata, or captured traffic. Modes: parsed (default) and stream. Not for source or remote-system changes.

Use when product copy needs buyer-objection evidence collected through approved, consented outreach. Not for unsolicited outreach or survey design.

Use when the user wants the current jargon weather of a domain described without advocacy. Not for choosing a positioning move: use buzzword-hijack.

Use when a user wants to choose and execute a bounded positioning move that rides a jargon wave. Not for describing the jargon weather of a domain: use buzzword-analysis.

Use when C code is written or audited and needs a pure-C baseline: standard, undefined behavior, integer and buffer safety, sanitizers, fuzzing, build flags. Not for C++: use modern-cpp-practices.

Use when the user requests a userspace C or C++ security review with a threat model and severity filter and wants validated findings. Not for kernel or bare-metal code: use kernel-security.

Use when the user asks "where to help", "contribution opportunities", or "find a good first issue". Returns data-backed first steps. Not for PR review queues: use gh-review-requests.

Use when the learner is ready to apply cleared concepts in a real project. Not for exercises or quizzes: use drill.

Use when evaluating Carbon for a C++ code base, running the carbon toolchain from a nightly or Bazel build, or comparing Carbon with staying on C++. Not for C++ modules: use cpp-modules.

Use when initializing, running, measuring coverage, or triaging a cargo-fuzz target in a Rust crate. Not for remote, credential, publish, deploy, or irreversible changes.

Use when managing Cargo workspaces, feature flags, build scripts, CI caching, dependency auditing, or Cargo.lock with Rust.

Use when prompt-doctrine is duplicated, drifted, or conflicting across output-style embeds and external harness AGENTS files. Not for editing the canonical baseline itself.

Use when the human returns after a gap, cannot follow the project, asks what happened, or wants a visual HTML recap page. Not for onboarding: use onboard. Not for handoff: use handoff.

Use when an Algorand, Cairo, Cosmos SDK, Solana, Substrate, or TON codebase needs vulnerability scanning with reachability-backed findings. Not for non-chain review: use security-review.

Use when a release or a since-tag window needs user-facing release notes drafted. Not for publishing the release.

Use when a human explicitly asks for a full repository agent-compatibility pass returning a scored report with prioritized fixes. Not for tasks that require source or remote-system changes.

Use when the user asks to cherry-pick, backport, or apply a hotfix to a release branch. Not for merging feature branches or cutting new release branches.

Use when the user explicitly asks to build, modify, or publish a Manifest V3 Chrome extension. Not for store submission without human-gated credentials.

Use when setting up or modifying CI/CD pipelines, quality gates, test runners, or deployment pipeline configuration through workflow files. Not for triggering a deployment.

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.

Implement issues (GitHub/GitLab/Bitbucket) using progressive analyze-specify-plan-implement workflow

Address PR/MR review feedback by reading comments, implementing fixes, and resolving threads. GitHub and GitLab support.

Retrospective analysis and improvement of workflow components with self-evolving patterns

Fix broken functionality from pasted error output, stack traces, or

Summarize recent git history since a baseline with structured analysis of what changed, why, and what to watch for.

Consolidate ephemeral LLM-generated markdown into permanent documentation.

Review pull requests with scope validation, code analysis, and line comments. Supports GitHub PRs and GitLab MRs.

Prepare a PR end-to-end by updating documentation, running tests, dogfooding checks, and validating with code review.

Batch-resolve unresolved PR/MR review threads via GraphQL API (GitHub/GitLab)

Detect and fix drift between plugin.json registrations and capabilities reference documentation

Update pre-commit hooks and CI/CD workflows based on recent project changes

Scan and update dependencies across all ecosystems with conflict detection

Update project documentation with consolidation, debloating, AI slop detection, capabilities sync, and accuracy verification.

Audit and sync plugin.json registrations with actual disk contents. Detects missing or stale skills, commands, agents, hooks.

Review and update test coverage using TDD/BDD methodology with quality validation. Generates tests for changed code.

Generate or update tutorials with VHS and Playwright recordings

Bump project versions using git-workspace-review and version-updates skills.

Generate and self-execute a diff-derived test plan for a PR. Reads

Generate new documentation with human-quality writing.

Clean up AI-generated content and improve documentation quality.

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…