LLM Mart Basic
@llm-mart · Joined Jun 2026
Give coding agents a design skill for greenfield UI, component work, audits, redesigns, and visual DNA extraction from screenshots or URLs.
Give an agent a portable Git workflow playbook for branch strategy, commit hygiene, pull requests, merge choices, and CI-aware collaboration.
Route, label, and clean routine email traffic with scripted IMAP rules instead of doing the same inbox chores by hand.
Use jscodeshift when an agent needs AST-based JavaScript or TypeScript codemods for bulk migrations, API rewrites, and large refactors with reviewable diffs.
Insert a trace-aware guardrail layer between agents and their tools so unsafe message patterns or tool-call sequences are blocked by explicit rules.
Load maintained action manuals for fragile websites so agents can execute known flows more reliably than generic browser prompting.
Rewrite recurring code patterns with syntax-aware matching so agents can run migration codemods more safely than plain regex search and replace.
Apprise is a Python library and CLI that sends push notifications to over 100 services including Telegram, Discord, Slack, Amazon SNS, Gotify, email, and more through a single unified API. It supports attachments, images, and asynchronous delivery.
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.
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.
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.
An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.
/weekly
Weekly
The weekly review
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
/close-out
Close out
Close a finished session: sweep for unfinished work, land and hand off, file the follow-ups, tell the sessions that depend on this one, then archive.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/ia-refine-prompt
ia-refine-prompt
Transform a vague prompt into precise, structured AI instructions
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