LLM Mart Basic

C patterns for systems code, libraries, and native extensions: module layout, function decomposition, status-enum errors, memory safety, undefined behavior, and performance measurement. Use when writing, reviewing, refactoring, or debugging C, working with malloc lifetimes, buffe

Structured code reviews with severity-ranked findings and deep multi-agent mode. Use when performing a code review, auditing code quality, or critiquing PRs, MRs, or diffs, including a diff or patch pasted inline. For the full multi-agent workflow, use the ia-review command (/ia-

Modern C++ patterns: RAII and ownership, rule of zero/five, exceptions and error handling, API and ABI boundaries, templates, and CMake tooling. Use when writing, reviewing, refactoring, or debugging C++, working with smart pointers, move semantics, memory leaks, template errors,

Systematic root-cause debugging with verification. Use for errors, stack traces, broken tests, flaky tests, regressions, or anything not working as expected. For validating bug reports before fixing, use bug-reproduction-validator agent.

Visual design and aesthetic direction for frontend interfaces. Use when building web pages, landing pages, dashboards, Next.js server components, or applications where visual identity matters. For React patterns and testing, use react-frontend.

Manage Git worktrees for isolated parallel development. Use when creating, listing, switching, or cleaning up git worktrees, or when needing isolated branches for concurrent reviews or feature work.

Defensive Bash scripting for Linux: safe foundations, argument parsing, production patterns, ShellCheck compliance. Use when writing bash scripts, shell scripts, cron jobs, or CLI tools in bash.

Manages project documentation: CLAUDE.md, AGENTS.md, README.md, CONTRIBUTING.md, DOCS.md. Use when asked to update, create, or init these context files. Not for general markdown editing.

Structured decision modifiers (/think, /verify, /adversarial, /edge, /confidence, /assumptions, etc.) to stress-test conclusions, evidence, assumptions, alternatives, and edge cases. Use when validating an important design, architecture decision, or ambiguous plan before committi

Node.js backend patterns: layered architecture, TypeScript, validation, error handling, security, observability, logging, metrics, deployment. Use when building REST APIs, REST endpoints, middleware, Express/Fastify/Hono/NestJS/Koa servers, tRPC procedures, Bun servers, or server

Modern PHP 8.4 and Laravel patterns: architecture, Eloquent, migrations, queues, testing. Use when working with Laravel, Eloquent, Blade, artisan, or building/testing a framework-based PHP app. Not for php-src internals, standalone PHP libraries, or general PHP language discussio

Pine Script v6: syntax, performance, error diagnosis, backtesting, visualization. Use when writing or debugging `.pine` files or TradingView Pine indicators/strategies.

Software implementation planning with optional file-based persistence. Use when asked to plan, when unresolved architecture or scope decisions need a durable record, or when multi-phase implementation needs recovery state. For the full research-and-issue workflow, use the ia-plan

PostgreSQL schema design, query optimization, indexing, and administration. Use when working with PostgreSQL, JSONB, partitioning, RLS, CTEs, window functions, or EXPLAIN ANALYZE.

Python patterns for CLI tools, async concurrency, and backend services. Use when working with Python code, building CLI apps, FastAPI services, async with asyncio, background jobs, or configuring uv, ruff, ty, pytest, or pyproject.toml.

React architecture patterns, TypeScript, Next.js, hooks, and testing. Use when working with React component structure, state management, Next.js routing, Vitest, React Testing Library, or reviewing React code. For visual design and aesthetic direction, use frontend-design instead

Process code review feedback critically: check correctness before acting, push back on incorrect suggestions, no performative agreement. Use when responding to PR/MR review comments or implementing reviewer suggestions received from others.

Session retrospective and skill audit. Use when asked to reflect, do a retrospective, review lessons learned, audit what went well or wrong, or review session effectiveness.

Rust patterns for CLI tools, backend services, and general application code. Use when working with Rust, Cargo workspaces, axum/tokio services, clap CLIs, async concurrency, or configuring clippy, rustfmt, cargo-nextest, or Cargo.toml.

Simplifies, polishes, and declutters code without changing behavior. Use when asked to simplify, clean up, refactor, declutter, remove dead code or AI slop, or improve readability. For analysis-only reports without code changes, use code-simplicity-reviewer agent.

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.

Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.

Refactor provided code for cleanliness, maintainability, and alignment with SOLID principles and modern best practices — no over-engineering.

Analyze and remediate technical debt — inventory debt items, score by impact, and produce a prioritized remediation plan with estimated effort.

Orchestrate comprehensive multi-dimensional code review using specialized review agents across architecture, security, performance, testing, and best practices

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

Execute tasks from a track's implementation plan following TDD workflow

Manage track lifecycle: archive, restore, delete, rename, and cleanup

Create a new track with specification and phased implementation plan

Git-aware undo by logical work unit (track, phase, or task)

Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)

Display project status, active tracks, and next actions

Restore saved project context and decisions to resume a session

Save project context, decisions, and progress for a later session

Build features guided by data insights, A/B testing, and continuous measurement

Design and implement batch and streaming data pipelines with ingestion, orchestration, dbt transformations, data quality checks, and monitoring

Reduce cloud costs across AWS, Azure, and GCP through rightsizing, reserved and spot capacity, storage tuning, and cost monitoring

Migration monitoring, CDC, and observability infrastructure

SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server

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

Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.

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A curated list of tools built for Jev — TypeSafe AI's System One model for typed decisions.

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Webextension tool for Odoo