LLM Mart Basic

Compiles and runs all PoCs for zeroize-audit findings. Produces poc_validation_results.json consumed by the verification agent and the orchestrator.

Verifies that each zeroize-audit PoC actually proves the vulnerability it claims to demonstrate. Reads PoC source code, finding details, and original source to check alignment between the PoC and the finding. Produces poc_verification.json consumed by the orchestrator.

Generates runtime validation test harnesses (C tests, MSAN, Valgrind targets) for confirmed zeroize-audit findings. Produces a Makefile for automated test execution.

Operate a caller-selected Gas City 1.4 with upstream registry packs and native run-centered surfaces while keeping GC runtime state out of AgentOps verdicts. Triggers: "using gc", "gas city", "drive the mayor", "dispatch through gc".

Execute one bounded RED to GREEN experiment from bead or caller intent; return derived subject identity and check facts. Triggers: "implement", "implement this bead", "run the experiment". Full plan-to-validation requests route to rpi.

Execute one bounded RED to GREEN experiment from bead or caller intent; return derived subject identity and check facts. Triggers: "implement", "implement this bead", "run the experiment". Full plan-to-validation requests route to rpi.

Freshly judge exact subject content against bead or caller acceptance, optionally persist verdict.v2 for a declared consumer, and stop. Triggers: "validate", "independently validate", "vibe".

Expert code review specialist. Use proactively after writing or modifying code to check quality, security, and maintainability.

Deep codebase exploration and analysis. Use for understanding code architecture, finding patterns, and gathering context before making changes.

Apply lean thinking to UX: hypothesis-driven design, collaborative sketching, and rapid experiments instead of heavy deliverables. Use when the user mentions "Lean UX", "design hypothesis", "outcome over output", "design studio method", "assumption mapping", "lightweight research

Engineer word-of-mouth and virality using the STEPPS framework (Social Currency, Triggers, Emotion, Public, Practical Value, Stories). Use when the user mentions "go viral", "word of mouth", "shareable content", "social currency", "why people share", "referral program", "nobody i

Navigate the technology adoption lifecycle from early adopters to mainstream market. Use when the user mentions "crossing the chasm", "beachhead segment", "whole product", "early adopters vs mainstream", "tech go-to-market", "bowling pin strategy", "technology adoption lifecycle"

Manage software complexity through deep modules, information hiding, and strategic programming. Use when the user mentions "module design", "API too complex", "shallow class", "complexity budget", "strategic vs tactical", "deep module", "information leakage", "pass-through method

Structure software around the Dependency Rule: source code dependencies point inward from frameworks to use cases to entities. Use when the user mentions "architecture layers", "dependency rule", "ports and adapters (hexagonal)", "onion architecture", "screaming architecture", "w

Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "deployment pipeline", "chaos engineering", "retry storm", "health checks", "my service keeps crashin

Assess whether to escalate models. Use when evaluating reasoning depth.

Detect friction signals; graduate patterns into rules. Use for session retrospectives.

Guide creating Claude Code hooks with security-first design. Use for validation and enforcement.

Select hook scope (plugin, project, global) by audience. Use when authoring a hook.

Evaluate hook security, performance, and SDK compliance. Use for audits.

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.

Create and manage database migrations

Analyze GitHub issue and create technical specification with implementation plan

Scaffold new feature with boilerplate code

Create a Jobs to be Done (JTBD) document for a product feature focusing on user needs

Create developer onboarding guide

Create a new branch, commit changes, and submit a pull request with automatic commit splitting

Create a Product Requirements Document (PRD) for a product feature

Create a comprehensive Product Requirement Prompt (PRP) with research and context gathering

Guide for creating pull requests using GitHub CLI with proper templates and conventions

Manage git worktrees for open PRs and create new branch worktrees

Manage cross-platform reference links

Systematically debug and fix errors

Analyze decision quality with scenario testing, bias detection, and team decision-making process optimization.

Explore decision branches with probability weighting, expected value analysis, and scenario-based optimization.

Audit dependencies for security vulnerabilities

Map and analyze project dependencies

Design optimized database schemas

Design RESTful API architecture

Create systematic digital twins with data quality validation and real-world calibration loops.

Analyze directory structure and purpose

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Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

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AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

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一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

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