LLM Mart Basic
@llm-mart · Joined Jun 2026
Federal Rules of Evidence expertise — auto-activates when assessing admissibility for depositions or trial
Legal research expertise — auto-activates when locating cases, statutes, and procedural rules for litigation tasks
Creating polished, client-facing consulting documents and presentations
Management consulting frameworks, structured problem-solving, and analytical thinking
Borrower education, rate explanations, closing process walkthroughs, and milestone updates
Loan products, rate structures, underwriting guidelines, compliance requirements, and closing procedures
Nursing assessment, NANDA-I taxonomy, NIC/NOC classification, medication administration documentation, and vital signs interpretation
Health literacy-adapted materials, teach-back method guidance, and discharge instructions
ADL assessment, fine motor evaluation, sensory processing, cognitive rehabilitation, and hand therapy documentation
Home program instructions, caregiver training materials, and adaptive equipment recommendations
Clinical optometry expertise for eye examination, ocular disease, contact lens fitting, and ophthalmic coding
Vision care education, treatment explanation, compliance counseling, and pediatric/geriatric communication adaptation
Legal research expertise including case analysis, statutory interpretation, and IRAC methodology
Legal writing expertise including contract drafting, legal memoranda, discovery, and correspondence
Exercise science expertise for program design, periodization, biomechanics, and evidence-based training methodology
Business strategies for client retention, pricing, marketing, and growth for solo fitness professionals
Clinical pharmacy expertise for medication therapy, drug information, and pharmacy practice
Patient-centered medication communication adapted to health literacy levels
Pricing strategies, proposal writing, contracts, client management, and studio operations
Shot composition guidance, album narrative structure, and brand photography direction
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.
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.
/changed-my-mind
Changed my mind
What I have revised
/claude-md
Claude md
Build or update your CLAUDE.md
/clusters
Clusters
Show what the vault is actually about
/commit
Commit
Commit the current state with a useful message
/commitments
Commitments
List open commitments
/compare
Compare
Compare two things from your own sources
/connect
Connect
Find the path between two ideas
/contradictions
Contradictions
List unresolved contradictions
/contradicts
Contradicts
Argue against me
/decisions
Decisions
List decisions made
/dedupe
Dedupe
Find near-duplicate pages
/doctor
Doctor
Check the setup is working
/draft
Draft
Draft from the vault
/dry-run
Dry run
Preview a run without writing
/explain
Explain
Explain it back and find the gaps
/export
Export
Export a page or set of pages
/gaps
Gaps
What is missing from my understanding
/graph-export
Graph export
Export the graph for outside analysis
/graph
Graph
Report the shape of the graph
/handoff
Handoff
Prepare a handoff brief
Atom Agent, Open-Source Governed AI Agent Platform for Self-Hosted Automation
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