LLM Mart Basic
@llm-mart · Joined Jun 2026
Inspect captured RAM images to enumerate processes, modules, handles, and suspicious in-memory behavior before escalation or evidence handoff.
Give Claude Code a video perception layer that extracts frames, transcribes audio, and lets Claude answer questions about local videos or YouTube URLs.
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.
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.
/smart-fix
Smart fix
Intelligent issue resolution with multi-agent debugging, root cause analysis, and verified fix implementation
/typescript-scaffold
Typescript scaffold
Scaffold a TypeScript project (Next.js, React with Vite, Node.js API, or library) with pnpm, testing, and dev tooling
/ai-assistant
Ai assistant
Build AI assistant application with NLU, dialog management, and integrations
/langchain-agent
Langchain agent
Create LangGraph-based agent with modern patterns
/prompt-optimize
Prompt optimize
Optimize prompts for production with CoT, few-shot, and constitutional AI patterns
/finetune
Finetune
Run the eval-gated fine-tuning lifecycle end to end — eval harness, method selection, data, environment, training, checkpoint gate, export
/promote-checkpoint
Promote checkpoint
Re-gate an existing fine-tuned checkpoint against the current eval harness and export it on PROMOTE
/ml-pipeline
Ml pipeline
Orchestrate specialized agents to build a production ML pipeline from data analysis through training, deployment, and monitoring
/find
Find
Quick gallery search. Use when user runs /meigen-ai-design:find with keywords to browse inspiration.
/gen
Gen
Quick image generation. Use when user runs /meigen-ai-design:gen with a prompt. Skips intent assessment, generates directly.
/multi-platform
Multi platform
Orchestrate cross-platform feature development across web, mobile, and desktop with API-first architecture
/monitor-setup
Monitor setup
Set up monitoring and observability with Prometheus metrics, Grafana dashboards, distributed tracing, log aggregation, and alerting
/slo-implement
Slo implement
Implement SLOs with SLI selection, error budgets, burn-rate alerting, dashboards, and reporting
/ai-review
Ai review
Run an AI-assisted code review that combines static analysis tools with AI review of security, performance, and architecture
/multi-agent-review
Multi agent review
Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review
/certify
Certify
Full quality certification with badge
/compare
Compare
Compare two skills head-to-head
/eval
Eval
Evaluate a plugin or skill for quality
/audit-chain
Audit chain
Verify every receipt in ./receipts/receipts.jsonl against the signer's public key. Detects tampered or malformed receipts across the audit trail.
/verify-receipt
Verify receipt
Verify a single Ed25519-signed receipt file against the signer's public key. Returns exit 0 if valid, 1 if tampered, 2 if malformed or the key is missing.
Atom Agent, Open-Source Governed AI Agent Platform for Self-Hosted Automation
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