LLM Mart Basic
@llm-mart · Joined Jun 2026
Angular is a TypeScript-based web application platform by Google providing dependency injection, declarative templates, a powerful CLI, and comprehensive libraries for routing, forms, and HTTP communication.
Diagnoses Ansible playbook failures using ansible-playbook --check --diff mode, ansible-lint, and the Ansible callback plugin API. Parses task execution results and suggests fixes for common module errors in ansible.builtin and community collections.
Runs Ansible diagnostic playbooks using ansible-runner and the Ansible Collections ecosystem (ansible.builtin, community.general). Captures system health, service status, and log analysis across inventory hosts.
Executes ansible-playbook --check --diff mode and parses the JSON callback output using the ansible.posix.json callback plugin. Identifies tasks that would change, predicts idempotency issues, and generates change impact reports.
Validates Ansible playbooks using ansible-lint and the Ansible Galaxy API. Performs check-mode dry runs, validates role dependencies, and detects deprecated module usage across collections.
Validates Ansible playbooks in check mode using ansible-playbook --check --diff and the Ansible Python API. Detects idempotency issues, undefined variables, and unreachable hosts before production runs.
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.
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.
/session-replay
session-replay
Convert a Claude Code or Codex session JSONL file into an animated replay of the conversation.
/session-to-post
session-to-post
Convert the current session's work into a shareable blog post, case study, or social thread.
/style-learn
style-learn
Extract writing style from exemplar text to create a reusable style profile.
/voice-extract
voice-extract
Extract your writing voice from samples into a reusable profile
/voice-generate
voice-generate
Generate text in your extracted writing voice
/voice-learn
voice-learn
Run learning pass on manually edited text to improve voice profile
/voice-review
voice-review
Review existing text against a voice profile
/record-browser
record-browser
Record browser sessions using Playwright
/record-terminal
record-terminal
Create terminal recordings with VHS tape scripts
/speckit-analyze
Speckit analyze
Cross-artifact consistency analysis across spec.md, plan.md, and tasks.md after task generation
/speckit-checklist
Speckit checklist
Generate a custom checklist for the current feature based on user requirements.
/speckit-clarify
speckit-clarify
Ask targeted questions to resolve spec ambiguities
/speckit-constitution
Speckit constitution
Create/update project constitution from principle inputs, syncing dependent templates
/speckit-converge
Speckit converge
Assess the codebase against spec, plan, and tasks, then append unbuilt work as new convergence tasks
/speckit-implement
Speckit implement
Execute the implementation plan by processing all tasks from tasks.md
/speckit-plan
Speckit plan
Execute implementation planning from spec to generate design artifacts.
/speckit-specify
Speckit specify
Create or update the feature specification from a natural language feature description.
/speckit-startup
Speckit startup
Bootstrap spec-driven development workflow at the start of a session
/speckit-tasks
speckit-tasks
Generate dependency-ordered tasks.md from design artifacts
/speckit-taskstoissues
speckit-taskstoissues
Convert tasks.md entries into GitHub Issues
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