LLM Mart Basic
@llm-mart · Joined Jun 2026
SST (Ion) infrastructure-as-code — TypeScript-first serverless on AWS with Pulumi, resource linking, and live Lambda dev
Infrastructure as Code with HashiCorp Terraform
AWS SDK v3 for TypeScript — modular clients, command pattern, S3, DynamoDB, SQS, Lambda, SNS, Secrets Manager
Cloudflare Workers edge compute platform — Wrangler CLI, KV, D1, R2, Durable Objects, Queues, Workers AI
Vercel deployment platform — project configuration, serverless/edge functions, Routing Middleware, cron jobs, environment variables, monorepo setup
Inspect a codebase, a stack the user describes, or a description of what they want to build; map what is there to agents-inc catalog skills — or intent to candidate built-in stacks the user picks from — and emit a SeedPayload plus a human-readable proposal report. Use when seedin
Composable component APIs — parts, state, polymorphism
Investigation flow (Glob -> Grep -> Read), evidence-based research with file:line references, structured output format for AI consumption. Use for pattern discovery, implementation research, and codebase investigation.
Backend specification planning frameworks. Use when a spec touches API endpoints, database schema, middleware, or auth. Covers endpoint contracts with request/response shapes, error catalogs, auth per endpoint, schema design with constraints and indexes, migration strategy, and m
CLI specification planning frameworks. Use when a spec touches a command surface, an interactive flow, config precedence, exit codes, or output modes. Covers flag contracts, prompt flow design, precedence tables, exit-code taxonomy, TTY/piped/JSON output, error text, signals, and
Frontend specification planning frameworks. Use when a spec touches UI components, forms, client state, or user-facing flows. Covers UI-state completeness (loading, error, empty, success), component boundaries, form validation contracts, state ownership, and measurable UI success
Backend code review patterns. Use when reviewing API routes, database operations, auth middleware, and server utilities. Covers injection, boundary validation, authorization coverage, secret/PII exposure, error leakage, and query patterns.
CLI code review patterns. Use when reviewing CLI applications built with Commander.js, @clack/prompts, picocolors. Covers exit codes, signal handling, error messages, user experience, testing adequacy.
Infrastructure code review patterns. Use when reviewing CI/CD workflows, Dockerfiles, deployment configs, and IaC. Covers supply-chain pinning, secret exposure, container hygiene, least-privilege permissions, and deployment safety.
Code review patterns, feedback principles. Use when reviewing PRs, implementations, or making approval/rejection decisions. Covers self-correction, progress tracking, feedback principles, severity levels.
UI component review patterns. Use when reviewing React components, hooks, props, state, styling, and accessibility. Covers rules of hooks, effect cleanup, render performance, list keys, keyboard and ARIA patterns.
React Native Gesture Handler - gesture types, GestureDetector, gesture composition, state machine, platform-specific gestures, swipeable rows, hover gestures
React Native Reanimated 4 - shared values, animated styles, spring/timing/decay, layout animations, gesture integration, scroll-driven animations, interpolation, worklets, CSS animations
React Native Skia GPU-accelerated 2D graphics - Canvas, declarative drawing, shaders, image filters, Paragraph text, Atlas batch rendering, Reanimated animations
Background fetch, processing tasks, background location, headless JS, battery optimization - Expo and bare React Native
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.
/setup
Setup
credo - Set up Claude Code with recommended workflows and plugins
/cleanup
Cleanup
dogma - Find and fix AI-typical patterns in code (reactive cleanup)
/docs-update
Docs update
dogma - Sync documentation across README files and wiki articles
/force
Force
dogma - Interactively collect and apply CLAUDE rules to the project
/ignore
Ignore
dogma - Add ignore patterns to multiple locations at once
/lint
Lint
dogma - Run project-specific linting and formatting on staged files (non-interactive)
/permissions
Permissions
dogma - Create or update DOGMA-PERMISSIONS.md interactively (Git, File, and Workflow permissions)
/sanitize-git
Sanitize git
dogma - Sanitize git history from Claude/AI traces and fix tracking issues
/sync
Sync
dogma - Intelligently sync Claude instructions from a source to the current project with interactive review
/versioning
Versioning
dogma - Check and fix version mismatches across all version files
/setup
gsd:setup
Install GSD resources into the active Claude config dir (${CLAUDE_CONFIG_DIR:-$HOME/.claude}/get-shit-done/) (required before using other GSD commands)
/uninstall
gsd:uninstall
Remove GSD resources from the active Claude config dir (${CLAUDE_CONFIG_DIR:-$HOME/.claude})
/cleanup
Cleanup
hydra - Remove already merged worktrees and their branches
/create
Create
hydra - Create a new Git worktree for isolated work
/delete
Delete
hydra - Safely remove a Git worktree
/help
Help
hydra - Show available commands and explain the concept
/list
List
hydra - List all Git worktrees of the repository
/merge
Merge
hydra - Merge a worktree branch back into current branch
/parallel
Parallel
hydra - Start multiple agents in parallel across worktrees
/spawn
Spawn
hydra - Start an agent in an existing worktree
Persistent session memory for AI coding agents — local-first, with on-device inference, associative recall, and drift detection. Works with Claude Code, Cursor,…
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