LLM Mart Basic
@llm-mart · Joined Jun 2026
Quantify cyber risk using FAIR methodology with Monte Carlo simulation, assess control effectiveness against NIST CSF/CIS/ISO 27001 frameworks, evaluate risk appetite alignment, and analyze cyber insurance coverage adequacy..
Audit transit damage prediction and prevention systems for packaging failure mode analysis, handling chain risk assessment, claims pattern detection, and protection level optimization..
Analyze debt payoff software — avalanche vs snowball strategy engines, interest calculation accuracy, amortization schedules, payment scheduling automation, credit score impact modeling, hardship accommodation workflows, and progress visualization.
Run multi-source web research with adversarial verification and produce a cited report: decomposes the question into 3-6 distinct queries (broad, specific, comparative, recency-anchored), searches and ranks sources by authority, recency, and specificity.
Analyze manufacturing defect detection and quality control systems — computer vision inspection pipelines, SPC control charts, Six Sigma process capability (Cp/Cpk), defect classification taxonomies, root cause analysis tooling, and measurement system analysis.
Analyze defense program budgets and acquisition costs — earned value management (EVM/CPI/SPI), should-cost modeling, PPBE process alignment, cost estimation per GAO guidelines, Nunn-McCurdy breach risk, FYDP profiles, and learning curve analysis. Audit DoD 5000 acquisition softwa
Analyze defense maintenance and readiness systems — MRO optimization, mission capable rate tracking, reliability-centered maintenance (RCM), condition-based maintenance (CBM+), depot-level analytics, configuration management, and workforce planning. Audit weapon system sustainmen
Analyze defense supply chain systems — DFARS compliance assessment, CMMC cybersecurity readiness, sole-source and DMSMS risk identification, counterfeit parts prevention per SAE AS6171, ITAR export control verification, and supplier tier mapping.
Analyze demand forecasting systems — time-series decomposition (ARIMA, Prophet, ETS), seasonal and event-driven demand modeling, booking curve and pickup analysis, cancellation prediction, forecast accuracy metrics (MAPE, bias), and model retraining pipelines.
Maps dependencies between stories, code modules, tickets, or specs. Computes optimal implementation order with parallel batches, cycle detection, and critical path analysis.
Analyze project dependencies for health, security, and bloat — audit outdated, deprecated, vulnerable, duplicate, heavy, and unused packages across npm, pip, cargo, go mod, and more. Produce a dependency health score, CVE inventory, license compatibility matrix, bundle size impac
Analyze disability services software — IEP and ISP management, person-centered planning workflows, HCBS Settings Rule compliance, accommodation tracking, assistive technology integration, EVV (Electronic Visit Verification), caregiver and DSP scheduling, and outcome measurement.
Audit a drug discovery pipeline for operational efficiency and scientific rigor. Triggers: building or reviewing pharma R&D platforms, cheminformatics pipelines, or screening data management systems.
Audit a dynamic pricing engine for revenue optimization and fairness. Evaluates price elasticity models, competitive intelligence feeds, promotional ROI, markdown optimization, price image management, and legal compliance including Robinson-Patman and price gouging regulations..
Audit an assisted living or elder care platform for resident safety and operational quality. Triggers: building or reviewing senior living software, nursing home management systems, or home health platforms.
Audit a 911 dispatch or emergency response system for operational reliability and compliance. Triggers: building or reviewing CAD systems, PSAP software, dispatch platforms, or emergency operations center tools.
Audit a job matching platform for relevance, fairness, and candidate experience. Triggers: building or reviewing job boards, ATS matching engines, internal mobility platforms, or workforce marketplaces.
Audit a manufacturing energy management system for monitoring quality, cost optimization, and compliance. Triggers: building or reviewing industrial energy platforms, building management systems, or sustainability reporting tools.
Audit a supply chain compliance system for ethical sourcing and labor rights. Triggers: building or reviewing supply chain compliance platforms, ESG reporting systems, or textile/garment sourcing tools.
Audit a tenant management system for eviction prevention and risk prediction. Triggers: building or reviewing property management platforms, affordable housing systems, or tenant services applications.
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.
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.
/bug-fix
Bug fix
Systematic workflow for fixing bugs including issue creation, branch management, and PR submission
/bulk-import-issues
Bulk import issues
Bulk import GitHub issues to Linear
/business-scenario-explorer
Business scenario explorer
Explore multiple business timeline scenarios with constraint validation and decision optimization.
/changelog-demo-command
Changelog demo command
Demo changelog automation features
/check-file
Check file
Perform comprehensive analysis of $ARGUMENTS to identify code quality issues, security vulnerabilities, and optimization opportunities.
/check
Check
Run project checks and fix any errors without committing
/ci-setup
Ci setup
Setup continuous integration pipeline
/clean-branches
Clean branches
Clean up merged and stale git branches
/clean
Clean
Fix all linting and formatting issues across the codebase
/code-permutation-tester
Code permutation tester
Test multiple code variations through simulation before implementation with quality gates and performance prediction.
/code-review
Code review
Perform comprehensive code quality review
/code-to-task
Code to task
Convert code analysis to Linear tasks
/code_analysis
Code analysis
Perform comprehensive code analysis with quality metrics and recommendations
/commit-fast
Commit fast
Automatically create and execute a git commit using the first suggested commit message
/commit
Commit
Create well-formatted git commits with conventional commit messages and emoji
/constraint-modeler
Constraint modeler
Model world constraints with assumption validation, dependency mapping, and scenario boundary definition.
/containerize-application
Containerize application
Containerize application for deployment
/context-prime
Context prime
Load project context by reading README.md and exploring relevant project files
/create-architecture-documentation
Create architecture documentation
Generate comprehensive architecture documentation
/create-command
Create command
Create a new command following existing patterns and organizational structure
Make any song you can imagine
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