LLM Mart Basic
@llm-mart · Joined Jun 2026
Audit workplace safety compliance systems for OSHA regulatory gap analysis, inspection readiness assessment, permit-to-work management, lockout/tagout program compliance, confined space entry procedures, and electrical safety evaluation..
Audit OSHA training compliance, certification expirations, competency tracking, and LMS integration. Triggers: you need to evaluate safety training programs, check ANSI Z490.
Audit whether a product is ready for enterprise sales. Use when you need to assess SSO/SAML/SCIM support, RBAC maturity, multi-tenancy data isolation, audit logging coverage, public API quality, SLA operational readiness, SOC2/ISO27001 certification gaps, GDPR data residency cont
Monitor SAM.gov federal contract opportunities (and follow-on awards) by NAICS, PSC, agency, set-aside, and keyword — produces a daily pipeline report with pursue/no-pursue scoring, capture-management cadence.
Autonomous SEO + AI-search optimization agent for 2026. Audits and fixes technical SEO, on-page metadata, structured data, Core Web Vitals (LCP/INP/CLS), llms.txt, Generative Engine Optimization (GEO) for ChatGPT/Perplexity/AI Overviews, E-E-A-T author signals.
Comprehensive 2026 SEO audit covering classic technical SEO (crawl, render, index, Core Web Vitals with INP), on-page (titles, meta, headings, internal linking), content (topical authority, entity density).
Generate a 2026-grade content brief for a target query — combines classic SERP analysis with AI Overview / Perplexity / ChatGPT citation analysis, entity recommendations (target ≥15 recognized entities), topical authority gap map, intent-mapped heading structure, internal linking
The full open SEO suite for 2026 — a single orchestrator that composes 10+ specialized sub-skills into a daily, weekly, and on-demand workflow that owns the SEO + GEO surface for a site..
Audit customer service triage systems for ticket routing, classification, and SLA compliance. Triggers: you need to evaluate ticket auto-classification accuracy, priority scoring models, skill-based routing logic.
Audit rehabilitation setback prediction systems for clinical risk modeling and early intervention. Triggers: you need to evaluate risk factor models (Charlson, Elixhauser), early warning indicators for functional decline.
Browser-based testing, validation, screenshots, recordings, and quick automation
Imported from alexei-led/cc-thingz/dist/claude/dev-flow/skills/committing-code.
Imported from alexei-led/cc-thingz/dist/claude/dev-flow/skills/documenting-code.
Imported from alexei-led/cc-thingz/dist/claude/dev-flow/skills/fixing-code.
Imported from alexei-led/cc-thingz/dist/claude/dev-flow/skills/improving-tests.
Imported from alexei-led/cc-thingz/dist/claude/dev-flow/skills/releasing-code.
Imported from alexei-led/cc-thingz/dist/claude/dev-flow/skills/reviewing-code.
Imported from alexei-led/cc-thingz/dist/claude/discovery/skills/brainstorming-ideas.
Imported from alexei-led/cc-thingz/dist/claude/discovery/skills/evolving-config.
Imported from alexei-led/cc-thingz/dist/claude/discovery/skills/installation-doctor.
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.
/deps-audit
Deps audit
Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.
/refactor-clean
Refactor clean
Refactor provided code for cleanliness, maintainability, and alignment with SOLID principles and modern best practices — no over-engineering.
/tech-debt
Tech debt
Analyze and remediate technical debt — inventory debt items, score by impact, and produce a prioritized remediation plan with estimated effort.
/full-review
Full review
Orchestrate comprehensive multi-dimensional code review using specialized review agents across architecture, security, performance, testing, and best practices
/pr-enhance
Pr enhance
Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report
/implement
Implement
Execute tasks from a track's implementation plan following TDD workflow
/manage
Manage
Manage track lifecycle: archive, restore, delete, rename, and cleanup
/new-track
New track
Create a new track with specification and phased implementation plan
/revert
Revert
Git-aware undo by logical work unit (track, phase, or task)
/setup
Setup
Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)
/status
Status
Display project status, active tracks, and next actions
/context-restore
Context restore
Restore saved project context and decisions to resume a session
/context-save
Context save
Save project context, decisions, and progress for a later session
/data-driven-feature
Data driven feature
Build features guided by data insights, A/B testing, and continuous measurement
/data-pipeline
Data pipeline
Design and implement batch and streaming data pipelines with ingestion, orchestration, dbt transformations, data quality checks, and monitoring
/cost-optimize
Cost optimize
Reduce cloud costs across AWS, Azure, and GCP through rightsizing, reserved and spot capacity, storage tuning, and cost monitoring
/migration-observability
Migration observability
Migration monitoring, CDC, and observability infrastructure
/sql-migrations
Sql migrations
SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server
/smart-debug
Smart debug
AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.
/deps-audit
Deps audit
Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.
PiG (Pi in Go) is a faithful Go port of upstream Pi, the TypeScript codebase behind the Pi coding agent. It is a parity-bound translation, not a rewrite: upstre…
1 views 0 likesAn AI Agent that lives in your pocket. Local-first and privacy focused.
2 views 0 likesUnofficial skill that teaches coding agents to build with TypeSafe AI's Jev: typed decisions, calibrated confidence, and prior art from 150+ community projects.
6 views 0 likesAdaptive Test-time Learning and Autonomous Specialization
4 views 0 likesPrediction-market trading engine — Wang Transform pricing on 291K+ contracts; paper-traded across Kalshi · Polymarket · Solana DFlow (Jito bundles) · 633 tests
3 views 0 likesKnowledge Management for Humans and Agents
5 views 0 likesOpen-source Claude Cowork / Codex / WorkBuddy alternative — a local-first AI office agent that turns one request into real PPTX, DOCX, XLSX and HTML files. Runs…
5 views 0 likesDeepAgent Code: AI coding agent with persistent memory and control plane
4 views 0 likesAwesome Jev — evidence-graded index of TypeSafe System One: SDKs, MCP tools, agents, apps and open models. 20 languages, rebuilt every 2 hours.
5 views 0 likesCLI for Telegram — agent-friendly, daemon-based, with webhook event push.
5 views 0 likesAI deep-research agent that turns any question into a cited report: plans searches, reads real sources, verifies evidence. Self-hosted, multi-provider, Docker-r…
4 views 0 likesEvent-stream AI Agent framework for building your persona bot 🍊
1 views 0 likesGive the agent a machine. Just not yours. Each AI coding agent gets its own isolated machine with root, Docker, and systemd - active defense detects and stops t…
3 views 0 likesLocal Emperor-style AI agent with Vue WebUI, multi-provider LLMs, streaming chat, tools, skills, memory, and token telemetry.
2 views 0 likesOpen-source AI reverse-engineering agent platform and MCP server for Ghidra, Frida, x64dbg and Rizin — automated PE/APK/binary analysis, CTF and malware researc…
8 views 0 likes"Never send a human to do a machine's job" - Open Source AI hacking agent
3 views 0 likesPrismer Cloud
3 views 0 likesMy Personal Blog (Robotics)
3 views 0 likesTau Coding Agent - like Pi, but twice as much
1 views 0 likesOpen-source alternative to OpenAI Dots: self-hosted AI chat, tools, approvals, connectors, and computer tasks.
0 views 0 likes