LLM Mart Basic

Audit transit damage prediction and prevention systems for packaging failure mode analysis, handling chain risk assessment, claims pattern detection, and protection level optimization..

Analyze debt payoff software — avalanche vs snowball strategy engines, interest calculation accuracy, amortization schedules, payment scheduling automation, credit score impact modeling, hardship accommodation workflows, and progress visualization.

Run multi-source web research with adversarial verification and produce a cited report: decomposes the question into 3-6 distinct queries (broad, specific, comparative, recency-anchored), searches and ranks sources by authority, recency, and specificity.

Analyze manufacturing defect detection and quality control systems — computer vision inspection pipelines, SPC control charts, Six Sigma process capability (Cp/Cpk), defect classification taxonomies, root cause analysis tooling, and measurement system analysis.

Analyze defense program budgets and acquisition costs — earned value management (EVM/CPI/SPI), should-cost modeling, PPBE process alignment, cost estimation per GAO guidelines, Nunn-McCurdy breach risk, FYDP profiles, and learning curve analysis. Audit DoD 5000 acquisition softwa

Analyze defense maintenance and readiness systems — MRO optimization, mission capable rate tracking, reliability-centered maintenance (RCM), condition-based maintenance (CBM+), depot-level analytics, configuration management, and workforce planning. Audit weapon system sustainmen

Analyze defense supply chain systems — DFARS compliance assessment, CMMC cybersecurity readiness, sole-source and DMSMS risk identification, counterfeit parts prevention per SAE AS6171, ITAR export control verification, and supplier tier mapping.

Analyze demand forecasting systems — time-series decomposition (ARIMA, Prophet, ETS), seasonal and event-driven demand modeling, booking curve and pickup analysis, cancellation prediction, forecast accuracy metrics (MAPE, bias), and model retraining pipelines.

Maps dependencies between stories, code modules, tickets, or specs. Computes optimal implementation order with parallel batches, cycle detection, and critical path analysis.

Analyze project dependencies for health, security, and bloat — audit outdated, deprecated, vulnerable, duplicate, heavy, and unused packages across npm, pip, cargo, go mod, and more. Produce a dependency health score, CVE inventory, license compatibility matrix, bundle size impac

Analyze disability services software — IEP and ISP management, person-centered planning workflows, HCBS Settings Rule compliance, accommodation tracking, assistive technology integration, EVV (Electronic Visit Verification), caregiver and DSP scheduling, and outcome measurement.

Audit a drug discovery pipeline for operational efficiency and scientific rigor. Triggers: building or reviewing pharma R&D platforms, cheminformatics pipelines, or screening data management systems.

Audit a dynamic pricing engine for revenue optimization and fairness. Evaluates price elasticity models, competitive intelligence feeds, promotional ROI, markdown optimization, price image management, and legal compliance including Robinson-Patman and price gouging regulations..

Audit an assisted living or elder care platform for resident safety and operational quality. Triggers: building or reviewing senior living software, nursing home management systems, or home health platforms.

Audit a 911 dispatch or emergency response system for operational reliability and compliance. Triggers: building or reviewing CAD systems, PSAP software, dispatch platforms, or emergency operations center tools.

Audit a job matching platform for relevance, fairness, and candidate experience. Triggers: building or reviewing job boards, ATS matching engines, internal mobility platforms, or workforce marketplaces.

Audit a manufacturing energy management system for monitoring quality, cost optimization, and compliance. Triggers: building or reviewing industrial energy platforms, building management systems, or sustainability reporting tools.

Audit a supply chain compliance system for ethical sourcing and labor rights. Triggers: building or reviewing supply chain compliance platforms, ESG reporting systems, or textile/garment sourcing tools.

Audit a tenant management system for eviction prevention and risk prediction. Triggers: building or reviewing property management platforms, affordable housing systems, or tenant services applications.

Analyze franchise expansion plans, model new market entry, score site selection candidates, map territory density, assess cannibalization risk, and build multi-year growth scenarios.

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.

Validate application configuration with schemas, per-environment rules, runtime checks, and secure handling of sensitive values

Preflight a DGX Spark system for an ML training or inference workload and emit env-report.json

Set up debugging and tracing with remote debugging, distributed tracing, debug logging, profiling, and production diagnostics

Generate API, architecture, code, and user documentation from a codebase and automate keeping it current

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.

Generate comprehensive migration plans and scripts for transitioning codebases between frameworks, languages, versions, or platforms with minimal disruption.

Plan and execute safe, incremental dependency upgrades with minimal risk — including breaking-change migration paths and proper test verification.

Orchestrate legacy system modernization using the strangler fig pattern with gradual component replacement

Scaffold React and React Native components with TypeScript, tests, styles, and Storybook stories

Scan React, Vue, Angular, and vanilla JavaScript code for XSS vulnerabilities and report fixes with secure coding examples

Orchestrate end-to-end full-stack feature development across backend, frontend, database, and infrastructure layers

Orchestrate git workflow from code review through PR creation with quality gates

Create a role-specific onboarding plan for a new team member, from pre-arrival setup through the first 90 days

Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report

Orchestrate multi-agent incident response with modern SRE practices for rapid resolution and learning

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

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

Agent Skills for Solopreneurs

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

Zero, your trustworthy AI teammate for real work.

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…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…