LLM Mart Basic

Audit contract management codebases for clause extraction accuracy, obligation tracking completeness, risk scoring model quality, renewal management, SLA monitoring, liability exposure, force majeure handling, and IP assignment detection..

Analyzes infrastructure costs at 1K-100K user scales by reading the actual codebase, auto-detecting cloud providers, modeling per-action costs, and projecting total monthly spend with optimization recommendations.

Audit construction project management software for budget tracking accuracy, earned value management (EVM) formula correctness, risk factor modeling, schedule-cost integration, change order workflow completeness, and early warning detection..

Generate an institutional-grade commercial real estate underwriting model — input schema (T-12 income, T-3 trailing, rent roll, debt terms, exit assumptions), calc engine (Cap Rate, NOI, Cash-on-Cash, IRR, DSCR, Debt Yield, ROI, Equity Multiple, levered & unlevered returns).

Audit credit risk modeling software for scoring algorithm accuracy, regulatory compliance (ECOA, FCRA, SR 11-7), bias and disparate impact testing, model governance lifecycle, and explainability..

Audit precision agriculture and crop management software for yield prediction model accuracy, soil analysis integration, irrigation optimization algorithms, pest and disease detection pipelines, satellite and drone imagery processing, weather data integration.

Audit curriculum management software for learning outcome alignment, pacing guide optimization, standards coverage mapping (Common Core, NGSS, state standards), differentiation support, assessment design quality, and content gap detection across grade levels and subjects..

Audit any product from a Customer Success Manager perspective -- evaluate onboarding flow completeness, self-service help infrastructure, customer health signal tracking, support channel accessibility, expansion and retention triggers, and customer communication systems.

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.

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.

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.

Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

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Android in docker solution with noVNC supported, video recording, mcp server and AI-agent