LLM Mart Basic

Analyze retail merchandising systems including planogram optimization (space-to-sales alignment, fair share index, sales per linear foot), visual merchandising effectiveness for in-store displays and e-commerce product pages, market basket analysis with association rule mining (A

Generate and maintain a multi-channel product feed across Google Merchant Center, Meta Catalog (Instagram + Facebook Shops), TikTok Shop, Pinterest Catalogs, Bing Shopping, and Snapchat Catalogs from a single product source of truth (Shopify, BigCommerce, WooCommerce, custom DB).

Computes development quality and velocity metrics from git history and tracks improvement over time. Measures fix ratios, rework hotspots, test coverage, DORA metrics, and code churn.

Analyze mining equipment maintenance systems including heavy fleet condition monitoring (oil analysis, vibration per ISO 17359/10816, thermal imaging), predictive analytics with Weibull reliability modeling and remaining useful life estimation.

Analyze mining safety management systems including incident investigation quality (ICAM, TapRooT, BowTie analysis), hazard identification and risk register completeness, critical control verification per ICMM framework, occupational health exposure monitoring (respirable dust, si

Generate MLS-compliant property listing copy in five length variants (tagline, MLS-short ≤250 char, MLS-long ≤4000 char, marketing description ~600-800 words, social caption) PLUS schema.org RealEstateListing JSON-LD for SEO/AEO syndication..

Analyze mobile app analytics implementation including event tracking completeness and naming conventions, SDK configuration audit (Firebase Analytics, Amplitude, Mixpanel, PostHog), attribution tracking with AppsFlyer/Adjust/Branch and SKAdNetwork conversion values.

Audit mobile app revenue implementation -- in-app purchases, subscriptions, ad SDKs, paywall design, trial conversion funnels, and store billing compliance. Triggers: reviewing IAP flows, optimizing subscription conversion, checking ad mediation setup.

Profile and audit mobile app performance -- cold/warm/hot startup time, memory leaks, battery drain, network efficiency, frame rate jank, and binary size. Triggers: diagnosing slow launches, investigating ANRs, reducing app size, or benchmarking rendering performance.

Audit mobile UX implementation against platform conventions -- navigation patterns, gesture handling, pull-to-refresh, infinite scroll, skeleton screens, haptic feedback, adaptive layouts, deep linking, and accessibility..

MVP analysis, product analysis, app teardown, analyze this app, what does this app do, product breakdown, feature analysis

Audit game narrative systems for technical quality -- branching dialogue trees, state/flag tracking, quest systems, choice-consequence mapping, localization pipelines, voice-over integration, and cinematic scripting..

Feature discovery agent — mines project docs, memory, user feedback, and competitor gaps to surface the highest-leverage features to build next. Outputs a prioritized feature backlog.

Map a cloud system against NIST SP 800-53 Rev. 5 + FedRAMP baselines to produce the documentation an authorization needs — System Security Plan (SSP), Control Implementation Summary (CIS), Plan of Action and Milestones (POA&M), Continuous Monitoring (ConMon) Plan..

Audit patient-facing healthcare software for portal feature completeness, secure messaging, health literacy, telehealth readiness, consent management, and HIPAA compliance. Triggers: evaluating a patient portal, checking PHI exposure in notifications, auditing telehealth flows.

Generate a production-grade Product Detail Page (PDP) optimized for the 2026 conversion benchmarks — 4-8% target vs 1.5-3% average. Triggers: "product page", "PDP", "product detail page", "Shopify product page", "ecommerce conversion".

Audit academic peer review operations -- reviewer matching algorithms, conflict of interest detection, turnaround time optimization, review quality scoring, and editorial workflow management..

Audit game analytics and telemetry implementation -- event tracking completeness, FTUE and monetization funnel coverage, retention metric infrastructure, A/B testing framework, heatmap data collection, churn prediction signals, and LTV modeling support..

Audit a codebase for product-market fit readiness -- evaluate startup PMF signals, core value loop tightness, feature scatter vs focus ratio, user activation funnel friction, retention hook infrastructure, pricing flexibility, analytics event coverage, CI/CD iteration speed, and

Audio file → full publishing kit pipeline. From a single .mp3 or .wav per episode, generates Whisper-large-v3 transcript with word-level timestamps, automatic chapter detection (audio scene change + topic shift), two show-notes lengths (scannable summary + long-form SEO).

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.

Assemble the governance record for a range — commits, overrides, ADRs, sprint auto-decisions, open questions, checkpoint findings — into one dated audit packet. Read-only.

Lightweight Q&A about the project — answer from context and return, no routing, no state change.

Periodic multi-reviewer sweep of the whole codebase — surfaces a triaged checkpoint report.

Sanctioned lane for non-behavioral work — docs-only edits, dependency bumps, reverts. Type-scaled gates; no TDD demanded of prose.

Clean up an already-merged local branch after proving containment. Confirm each discard and preserve unique work.

Show the codeArbiter command catalog — the public command list and what each routes to.

Create a verified local Git commit when committing changes is requested. Not for explaining commit history, drafting a message only, or postponing a commit. Applies every commit gate and never implies a push or PR.

Stop everything and surface a rule conflict — persona vs. docs vs. code. Present both sides and the conflict-hierarchy level; the user resolves. No silent reconciliation.

Audit stale provenance-tracked docs on request. Report first; re-scout or re-baseline only for selected docs.

Build project context from an existing codebase through isolated scouts, resolve gaps, and preserve initialization gates.

Investigate an unexplained defect or unexpected behavior without changing application code. Use for root-cause diagnosis and an evidence-backed handoff. A no-action close records a board note. Not for implementing a known fix, new features, or explanation-only questions.

Develop greenfield project context through a layered interview, preserve decisions, and initialize only after the required gates.

Verify the active host install, package, command ownership, enforcement, and harmless live-fire probe. Read-only.

Start a feature: brainstorm a spec, get it approved, then drive it test-first through the pipeline. The one entry to implementation.

Fix a confirmed bug: a failing regression test first, then a minimal fix, then the rest of the tdd gates.

Opt this repo into codeArbiter — scaffold the root-level .codearbiter/ state store.

Read-only 3-metric governance glance — override rate, small-lane rate, sprint low-confidence ratio — each with a trend arrow vs. the prior 20-commit window.

Sanctioned, logged bypass of a gate or hard rule — one audit line, then proceed.

Open a PR or finish branch disposition; route CI watching and post-merge cleanup to their owners. Merge and discard need explicit authority.

Zero-onboarding, read-only dry-run of the reviewer fleet against the current uncommitted diff. Predicts reviewers, runs the state-free secret scan, writes nothing.

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…