LLM Mart Basic
@llm-mart · Joined Jun 2026
Validates Ansible playbooks and roles using ansible-lint and yamllint APIs. Enforces best practices for idempotency, variable naming, and handler usage with custom rule profiles.
Validates Ansible playbooks using ansible-lint with custom rule plugins and the Ansible Collections API. Checks for deprecated modules, missing handlers, insecure variable practices, and role dependency conflicts.
Imported from agentskillexchange/skills/skills/ansible-playbook-runner.
Generates Ansible playbook YAML with proper module usage, handler chains, and role structures using ansible-core built-in modules. Supports Jinja2 template rendering and vault-encrypted variable files.
Generates and validates Ansible playbooks from infrastructure requirements. Uses ansible-lint for validation and queries Ansible Galaxy API for discovering certified roles and collections.
Executes Ansible playbooks against dynamic inventories from AWS EC2 or Azure, decrypting Ansible Vault secrets via HashiCorp Vault KV v2 API. Streams task output in real time and posts a per-host pass/fail summary to Slack. Supports --check mode for dry-run validation before live
Executes Ansible playbooks for server diagnostics and remediation using ansible-runner Python SDK. Supports inventory parsing, vault-encrypted credentials, and real-time task output streaming.
Instruments Anthropic API calls to log token usage, latency, and cost per request using the Anthropic TypeScript SDK. Wraps the anthropic.messages.create method to capture usage.input_tokens, usage.output_tokens, and timing from the API response. Writes structured logs to CloudWa
Anyquery is a SQL query engine that lets you run SQL against 40+ apps, files, and databases including GitHub, Notion, Chrome, and Apple Notes. Built on SQLite with MCP server support for connecting AI agents to structured data across services.
Imported from agentskillexchange/skills/skills/apache-airflow-mcp.
Manages Apache Avro schema evolution with compatibility checking via Confluent Schema Registry API. Validates forward, backward, and full compatibility across schema versions automatically.
Maps and transforms data between systems using Apache Camel route definitions and the Camel Component API. Supports XSLT, JSONPath, and DataFormat transformations via camel-core SDK.
Diagnoses Kafka consumer group lag using the Kafka AdminClient API and JMX metrics exposed via the Confluent Metrics API. Identifies slow consumers, topic partition hotspots, and broker rebalance storms that contribute to lag growth. Provides a step-by-step runbook to tune fetch.
Extracts and transforms Avro, Protobuf, and JSON Schema definitions from Confluent Schema Registry. Generates typed data models and validates schema compatibility using the Schema Registry REST API.
Imported from agentskillexchange/skills/skills/apache-kafka-stream-processor.
Processes real-time event streams using KafkaJS consumer groups and transforms messages with configurable schemas. Handles partition rebalancing, offset commits, and dead-letter queue routing for failed transformations.
Imported from agentskillexchange/skills/skills/apache-spark-job-manager.
Apache Superset is a widely adopted open-source BI platform for SQL exploration, chart building, and dashboard delivery. This skill is useful when an agent needs to query warehouse data, assemble dashboards, or explain metrics using a mature analytics interface instead of ad hoc
Extracts text and metadata from 1400+ file formats via Apache Tika Server REST API. Handles PDF, DOCX, PPTX, email archives, and embedded document extraction with MIME type detection.
Wraps Apache Tika Server REST API for extracting structured text from PDFs, DOCX, PPTX, and 1,200+ file formats. Outputs clean markdown with metadata preservation using Tika /rmeta/text endpoint and recursive parsing mode.
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.
A green PR, a controller reporting success, and not one line of the new code running
/compare
Compare
Compare two things from your own sources
/connect
Connect
Find the path between two ideas
/contradictions
Contradictions
List unresolved contradictions
/contradicts
Contradicts
Argue against me
/decisions
Decisions
List decisions made
/dedupe
Dedupe
Find near-duplicate pages
/doctor
Doctor
Check the setup is working
/draft
Draft
Draft from the vault
/dry-run
Dry run
Preview a run without writing
/explain
Explain
Explain it back and find the gaps
/export
Export
Export a page or set of pages
/gaps
Gaps
What is missing from my understanding
/graph-export
Graph export
Export the graph for outside analysis
/graph
Graph
Report the shape of the graph
/handoff
Handoff
Prepare a handoff brief
/health
Health
Quick health check
/hubs
Hubs
Find pages that swallowed the graph
/index
Index
Rebuild the index
/ingest-chats
Ingest chats
Import an exported chat history
/ingest-highlights
Ingest highlights
Ingest book or article highlights
Make any song you can imagine
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