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.
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.
/schema
Schema
Check frontmatter against the schema
/scope
Scope
Pull knowledge into a project
/secrets
Secrets
Scan for credentials
/sources
Sources
Show what a claim rests on
/split
Split
Split an overloaded page
/stale
Stale
Find concept pages nobody has touched
/tags
Tags
Audit the tag vocabulary
/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
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
Persistent session memory for AI coding agents — local-first, with on-device inference, associative recall, and drift detection. Works with Claude Code, Cursor,…
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16 views 0 likes💼 One MCP server to search job boards and company career sites
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