LLM Mart Basic
@llm-mart · Joined Jun 2026
Appsmith is an open-source platform for building internal tools, dashboards, and admin panels on top of databases and APIs. It is well suited to operational workflows where agents or developers need a fast way to stand up interfaces for support, ops, analytics, or back-office tas
Appwrite is an open-source, self-hosted backend platform that provides authentication, databases, storage, functions, messaging, and realtime APIs out of the box. It serves as a privacy-first alternative to Firebase and Supabase, packaged as Docker microservices for full data own
Appwrite is an open-source backend platform for web, mobile, and AI apps. This skill helps agents use Appwrite's real services—Auth, Databases, Storage, Functions, Messaging, Realtime, and Sites—instead of inventing a generic backend workflow.
Use photo-cli when an agent needs to normalize a local photo archive by reading capture metadata, reverse geocoding locations, and rebuilding a cleaner folder structure without moving into a hosted photo platform.
Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.
Calls Adobe Firefly's text-to-image and generative fill APIs for batch asset creation. Manages Adobe IMS OAuth tokens and enforces Content Credentials (C2PA) metadata on all outputs.
Download a supported video URL with yt-dlp and upload the preserved file plus metadata to archive.org as a repeatable preservation job.
Analyzes Argo Workflows DAG templates to identify parallelization opportunities. Uses the Argo Server API to fetch workflow execution history and critical path analysis.
Constructs Kubernetes-native workflow DAGs using Argo Workflows CRDs with configurable retry strategies, artifact passing via S3/MinIO, and template composition through WorkflowTemplates and ClusterWorkflowTemplates.
Orchestrates deployment pipelines using the Argo Workflows Engine API and Argo CD ApplicationSet controller. Implements progressive delivery with Argo Rollouts canary and blue-green strategies.
Lints and validates Argo Workflows templates using the argo CLI and Argo Server REST API. Detects DAG dependency cycles, invalid artifact references, and parameter type mismatches across workflow steps.
Manages ArgoCD application deployments via the ArgoCD REST API and argocd CLI. Configures GitOps sync policies, automated rollbacks, and multi-cluster application sets with generator templates.
Diagnoses ArgoCD application sync failures and degraded states using the ArgoCD REST API and argocd CLI. Queries /api/v1/applications/{name} for sync status, resource health, and operation state. Provides automated remediation steps for OutOfSync, Degraded, and Missing resource c
Manages ArgoCD application synchronization using the ArgoCD REST API and argocd CLI. Handles sync waves, hooks, and health assessments for GitOps-driven Kubernetes deployments.
Monitors ArgoCD application sync status via the ArgoCD REST API and argocd CLI. Detects OutOfSync conditions, tracks sync wave progress, and alerts on failed sync operations with detailed resource diff analysis using argocd app diff.
Monitors ArgoCD application deployments using the ArgoCD REST API and gRPC interface. Tracks sync status, health checks, and rollback history across Kubernetes namespaces.
Manages GitOps deployments using ArgoCD API, argocd CLI, and Kustomize overlays. Automates sync operations, rollback procedures, and application health monitoring.
Manages GitOps deployments via the ArgoCD REST API and argocd CLI. Triggers application syncs through /api/v1/applications/{name}/sync, monitors health status via /api/v1/applications/{name}, and manages rollbacks using /api/v1/applications/{name}/rollback for Kubernetes workload
Automates ArgoCD application synchronization using the ArgoCD gRPC/REST API and argocd-autopilot CLI. Manages ApplicationSets, sync waves, and health assessments for Kubernetes deployments.
Manages ArgoCD Application and ApplicationSet resources for Kubernetes GitOps deployments. Uses the ArgoCD REST API and argocd CLI to automate sync waves, health checks, and progressive rollout configurations.
An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.
Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.
Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.
Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.
Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.
Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.
A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.
Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.
Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.
AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.
AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.
A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.
One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.
"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.
A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.
The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.
Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.
Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.
A green PR, a controller reporting success, and not one line of the new code running
/chore
Chore
This is the lane for changes with no behavior to test-drive — prose edits, a version bump on an
/cleanup
Cleanup
Use this after a pull request has merged but your local checkout is still on the topic branch.
/commands
Commands
Prints the public command catalog straight from `COMMANDS.md` — the plugin's own single source
/commit
Commit
This is the single entry point for turning staged work into a commit — nothing in codeArbiter
/conflict
Conflict
The protocol for a rule conflict — not a skill route, an orchestrator-level halt. When two sources
/context-check
Context check
An optional, on-demand drift audit for the bypass case: a merge, a direct push, or a manual edit
/create-context
Create context
This is the populator for a project that already has code to read. Instead of interviewing you about
/debug
Debug
This is where an unexplained defect goes before anyone touches code. The investigation is
/decompose
Decompose
This is the populator for a project that has no code yet to read. Rather than guessing at
/doctor
Doctor
Proves the install is actually enforcing, rather than just present. codeArbiter's worst failure
/feature
Feature
This is the standard entry point for new work with a human in the loop at every step. A short
/fix
Fix
This is the entry point for a defect that already has a known cause, or one you can describe
/init
Init
This is how a repository opts into codeArbiter for the first time. It writes the root-level state
/metrics
Metrics
A bare-numbers governance glance — three metrics, each with a trend arrow against the prior
/override
Override
The sanctioned, logged escape hatch. A routine gate — a lint rule, a style check, a non-security
/pr
Pr
Explicit PR entry and a direct request to open a PR use the same branch-finishing owner.
/preview
Preview
A zero-onboarding, read-only dry-run of the reviewer fleet against whatever is currently
/prune
Prune
This is a Feature Forge preview command — the after-each-turn service ships **off** by default and
/reconcile
Reconcile
Compares architectural records with the scaffold and prior decisions using SMARTS.
/refactor
Refactor
This is the lane for moving or reshaping code without changing what it does — a rename, an extract,
Make any song you can imagine
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