LLM Mart Basic
@llm-mart · Joined Jun 2026
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
Musculoskeletal and neurological rehabilitation expertise for physical therapy documentation and clinical reasoning
AI infrastructure and governance readiness — auto-activates when scoping or launching AI features
Competitive intelligence for AI product launches — auto-activates when benchmarking AI features, pricing, or positioning
Prompt-engineering expertise for designing test cases, edge cases, adversarial inputs, and iterating on prompts based on eval results
Skill and prompt benchmarking expertise for measuring latency, accuracy, token cost, and token-budget compliance across variants
Professional board reporting, financial presentation, compliance documentation, and resident communication
Property management expertise including fair housing law, lease administration, HOA governance, and vendor management
Real estate client relationship communication for buyers, sellers, and leads
MLS listing writing, social media marketing, and Fair Housing Act compliance for real estate
Pattern recognition for LLM-generated resume text — sentence length variance, em-dash density, and generic accomplishment phrasing
Employer branding expertise for EVP communication, DEI-inclusive language, and candidate experience
Auto-activates ghost-job red-flag detection on job postings, ATS pipeline indicators, and pay-transparency gaps
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.
/timeline
Timeline
How my sources developed over time
/trace
Trace
Show which pages an answer used
/typed-links
Typed links
Add relation types where they matter
/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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