LLM Mart Basic
@llm-mart · Joined Jun 2026
Use when "launch plan", "go-to-market", "GTM strategy", "how to launch", "launch checklist", "growth plan", or product is built and needs distribution strategy. Do NOT use for content generation (/content-gen) or SEO audit (/seo-audit).
Use when "privacy policy", "terms of service", "legal pages", "GDPR", "CCPA", "app store legal", or project needs compliance documents. Do NOT use for NDA or contracts.
Use when "audit memory", "check CLAUDE.md", "memory map", "rules audit", "context budget", "what loads in my session", or need to optimize agent context loading.
Use when "set up metrics", "track KPIs", "PostHog events", "funnel analysis", "when to kill or scale", "success metrics", or need analytics plan. Do NOT use for SEO metrics (/seo-audit).
Take a trained neural model to devices — ONNX export, int8 quantization, Core ML conversion, on-device benchmarking, download-on-demand delivery. Use when user says "сожми модель", "quantize the model", "convert to Core ML / ONNX", "model is too big for the app", "run the model o
Use when "run pipeline", "automate research to PRD", "full pipeline", "research and validate", "scaffold to build", "loop until done", "chain skills", or need multi-skill automation. Do NOT use for single skills (use the skill directly).
Use when "plan this feature", "create implementation plan", "write a spec", "battle plan", describing a feature/bug/refactor, or need task breakdown before building. Do NOT use for idea validation (/validate) or execution (/build).
Use when "reddit comment", "engage reddit", "build karma", "post to reddit", or need to participate in Reddit threads. NOT for thread discovery (/community-outreach) or social copy (/content-gen).
Use when "research this idea", "find competitors", "check the market", "domain availability", "market size", "analyze opportunity", or need evidence before validation. Do NOT use for idea scoring (/validate) or SEO auditing (/seo-audit).
Use when "retro", "evaluate pipeline", "what went wrong", "pipeline review", "check pipeline logs", or after pipeline completes and needs quality assessment.
Use when "review code", "quality check", "is it ready to ship", "final review", or after /build or /deploy completes. Do NOT use for planning (/plan) or building (/build).
Use when "scaffold project", "create new project", "start new app", "bootstrap project", "set up from PRD", or need project from PRD + stack template. Do NOT use for planning features (/plan) or PRD generation (/validate).
Use when "check SEO", "audit this page", "SEO score", "check meta tags", "SERP position", or need website SEO health check. Do NOT use for landing content (/landing-gen) or social media posts (/content-gen).
Use when "set up workflow", "configure TDD", "wire up dev workflow", or after /scaffold before /plan to generate workflow config. Do NOT use for founder setup (/init) or scaffolding (/scaffold).
Use when "design schemas", "structured output", "agent loop", "SGR", "constrained decoding", "tool dispatch", "Pydantic schema for LLM", or need to design a schema-guided reasoning pipeline for an agent or API. Do NOT use for general code review (/review) or planning (/plan).
Use when "audit skill", "review skill quality", "check skill", "skill score", "skill checklist", "is this skill good", or evaluating skill against best practices. Do NOT use for KB audits (/audit) or code review (/review).
Use when "help me decide", "should I do this", "evaluate decision", "STREAM analysis", "run decision framework", "pros and cons", or facing a high-stakes founder choice. Do NOT use for idea validation with PRD (/validate).
Use when "swarm research", "parallel research", "investigate fast", "3 agents", "team research", or want faster multi-angle alternative to /research. Do NOT use for solo research (/research) or idea scoring (/validate).
Build and hold a SwiftUI design system — a 12-column grid, spacing/type/radius/motion scales, surface levels, a component gallery, and the guards that stop it drifting back. Use when the user says "сделай по сетке", "дизайн-система", "разъезжается вёрстка", "магические числа в pa
Use when "validate idea", "score this idea", "should I build this", "go or kill", "generate PRD", "evaluate opportunity", or need idea scoring with PRD output. Do NOT use for deep research (/research first) or decision-only framework (/stream).
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.
/requirements
Requirements
Generate requirements from goal and research
/research
Research
Run or re-run research phase for current spec
/start
Start
Smart entry point that detects if you need a new spec or should resume existing
/status
Status
Show all specs and their current status
/switch
Switch
Switch active spec
/tasks
Tasks
Generate implementation tasks from design
/triage
Triage
Decompose a large feature into multiple dependency-aware specs (epic triage)
/tree-ring-update
Tree ring update
Check for or install a verified Tree Ring Memory CLI update without changing installation scope
/README
README
This directory contains the command implementations for the fast-agent CLI.
/close
Close
They operate it without you.
/outcome
Outcome
Promised, measured, accepted. A number nobody signed is claimed, not delivered.
/prep
Prep
Prepare the meeting. One page from the record.
/receipts
Receipts
Find the receipt. A dated line, or it did not happen.
/trust
Trust
Diagnose trust. Process gap, or they stopped trusting you.
/awesome-docs
awesome-docs
Generate, convert, and maintain animated GitHub-safe Markdown documents with animated SVG diagrams. Covers four SVG patterns (architecture flow, lifecycle loop, field carousel, timeline phases), guided interview for any doc type (README, architecture guide, runbook, API reference, tutorial, RFC, post-mortem, how-it-works, or custom), converting existing plain Markdown, diffing for stale diagrams, quality auditing, local preview, and multi-platform export. Use when asked to "create a README for X", "write an architecture doc", "animate this guide", "convert my doc to animated", "check if my diagrams are stale", or "export my doc for Confluence".
/aws-profile
aws-profile
AWS profile management for MCP servers — discover profiles across SSO, Granted, and assumed-role chains, check credential TTL, switch profiles across VS Code and Claude Code MCP configs, and scan AWS Organization accounts.
/aws
aws
Structured guidance for AWS CloudFront distributions, WAF web ACLs, Lambda@Edge, CloudFront Functions, Firewall Manager multi-account enforcement, and IAM/IRSA patterns. Covers OAC, cache policies, security headers, managed rule groups, rate limiting, FMS FIRST/MIDDLE/LAST ownership model, and production-ready Terraform generation.
/azure
azure
Azure identity (Workload Identity, OIDC, Entra ID), resource tagging, AKS platform patterns, RBAC scoping, and production-readiness review — with Terraform generation.
/chaos
chaos
Design, run, and debug Chaos Engineering experiments on Kubernetes using Litmus Chaos v3 and Chaos Mesh v2. Covers fault injection (pod-delete, network-loss, CPU stress, node-drain), steady-state hypothesis probes, GameDay runbooks, scheduled experiments, DORA feedback loop, and RBAC setup. Use when asked to "inject a pod fault", "run a GameDay", "schedule chaos experiments", or "debug why my ChaosEngine is stuck".
/checkov
checkov
Bootstrap Checkov on a developer laptop, run static or plan-level Terraform security scanning for AWS/Azure/GCP/EKS, resolve private GitHub modules via gh CLI, generate pre-commit hooks, produce multi-format output (cli/json/sarif/junit), and fix violations with AI-generated patches. Use when asked to "scan my Terraform", "run checkov", "check my IaC for security issues", "set up checkov pre-commit", or "fix checkov findings".
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间,让人与智能体在此协作
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