LLM Mart Basic
@llm-mart · Joined Jun 2026
Machine learning in Python with scikit-learn. Use for classification, regression, clustering, model evaluation, and ML pipelines.
Seaborn is a Python visualization library for creating publication-quality statistical graphics. Use this skill for dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and complex multi-panel figures with minimal code.
Comprehensive security auditing workflow covering web application testing, API security, penetration testing, vulnerability scanning, and security hardening.
Coordinate multi-layer security scanning and hardening across application, infrastructure, and compliance controls.
Seek and analyze video content using Memories.ai Large Visual Memory Model for persistent video intelligence
Automate Segment tasks via Rube MCP (Composio): track events, identify users, manage groups, page views, aliases, batch operations. Always search tools first for current schemas.
Automate Sentry tasks via Rube MCP (Composio): manage issues/events, configure alerts, track releases, monitor projects and teams. Always search tools first for current schemas.
Run a broad SEO audit across technical SEO, on-page SEO, schema, sitemaps, content quality, AI search readiness, and GEO. Use as the umbrella skill when the user asks for a full SEO analysis or strategy.
Writes long-form blog posts with TL;DR block, definition sentence, comparison table, and 5-question FAQ for SEO ranking and AEO citation. Activate when the user wants to write a blog post, article, or long-form content piece.
Builds a topical authority map with a pillar page, prioritised cluster articles, content types, internal link map, and content gap analysis. Activate when the user wants to build a content cluster, topic map, or content strategy.
Audits content for SEO and AEO performance with scored reports, severity-ranked fix lists, and projected scores after fixes. Activate when the user wants to audit, review, or score content for SEO or AEO compliance.
Maps internal link opportunities between pages with anchor text, placement instructions, orphan page detection, and cannibalization checks. Activate when the user wants to build an internal linking strategy or find link opportunities.
Researches and prioritises SEO keywords with AEO question queries, difficulty tiers, cannibalization checks, and a content map. Activate when the user wants to find keywords, research search terms, or build a keyword strategy.
Writes complete, structured landing pages optimized for SEO ranking, AEO citation, and visitor conversion. Activate when the user wants to write or generate a landing page for a product, service, or offer.
Writes 3 title tag variants and 3 meta description variants per page with SERP preview, OG tags, and Twitter Card tags. Activate when the user wants to write meta tags, title tags, or social sharing tags for any page.
Generates valid JSON-LD structured data for 10 schema types with rich result eligibility validation and implementation-ready script blocks. Activate when the user wants to generate schema markup, JSON-LD, or structured data for any page.
Diagnose and audit SEO issues affecting crawlability, indexation, rankings, and organic performance.
'Analyzes content for E-E-A-T signals and suggests improvements to
Analyzes multiple provided pages to identify keyword overlap and potential cannibalization issues. Suggests differentiation strategies. Use PROACTIVELY when reviewing similar content.
Generate SEO-optimized competitor comparison and alternatives pages. Covers "X vs Y" layouts, "alternatives to X" pages, feature matrices, schema markup, and conversion optimization. Use when user says "comparison page", "vs page", "alternatives page", "competitor comparison", or
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
Atom Agent, Open-Source Governed AI Agent Platform for Self-Hosted Automation
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