Comprehensive container image security scanning and remediation. Analyzes Docker images for OS package vulnerabilities, application dependencies, and Dockerfile best practices. Use when: - User asks to scan a Docker image or container - User mentions "container security" or "image vulnerabilities" - User wants to secure a Dockerfile - User asks about base image security - Agent is working with Docker, Kubernetes, or container deployments

Collecting and synthesizing user feedback across channels (support tickets, NPS, in-app feedback, sales calls, social mentions, customer councils) into a continuous signal that informs product decisions. The triage discipline that distinguishes loudest-voice (whoever complains most wins) from averaged-noise (every signal weighted equally) from triaged-synthesis (signal weighted by source quality, frequency, and decision relevance). Triggers on user feedback, customer feedback aggregation, NPS, support ticket analysis, customer councils, feedback synthesis, voice of customer, feedback triage, in-app feedback. Also triggers when feedback channels overflow with volume that does not produce decisions, when the loudest-voice problem is steering roadmap, or when continuous feedback streams need synthesis discipline.

How to design and run a programmatic SEO program that produces durable traffic instead of penalty-bait. Data source identification, template design, schema patterns, quality control at scale, internal linking architecture, crawl budget management, AEO/GEO for programmatic pages, refresh discipline, and the make-or-break question of whether pSEO is the right answer for your program at all. Triggers on programmatic SEO, pSEO, scaled content, page generation, template SEO, location pages, comparison pages, directory site, listing site, scaled landing pages, programmatic content. Also triggers when a content set is not ranking, has been hit by an algorithm update, or when a team is considering pSEO as a growth lever.

MemPalace — mine projects and conversations into a searchable memory palace. Use when asked about mempalace, memory palace, mining memories, searching memories, or palace setup.

Answer questions about Tactical RMM (TRMM) — an open-source remote monitoring and management platform. Covers architecture, installation, agent deployment (Windows/Linux/macOS), MeshCentral integration, scripting (PowerShell/Python/Bash/Deno), script variables, custom fields, keystore, automated checks, tasks, automation policies, maintenance mode, alerting, email/SMS notifications, webhooks, REST API, global settings, overrides, permissions, Django admin, URL actions, user interface, software management, web terminal, management commands, reporting (Enterprise), SSO (Enterprise), third-party integrations (Bitdefender, Zammad), SNMP checks, BitLocker key retrieval, remote background sessions, and troubleshooting FAQ.

Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.

Release engineering. Diagnose and fix CI/CD failures, get to green, cut releases, manage versioning and changelog notes. Pragmatic about getting changes safely into production — not perfect, shipped.

Confirm a story is actually done. Walk acceptance criteria against the implementation, check test coverage at the right layer, identify edge cases the tests miss. Adversarial about "done" — does not take coverage claims on trust.

Provides templates, style guidelines, and a complete workflow for writing MkDocs documentation, sample pages, and navigation updates for BlazorWebFormsComponents. Covers component doc structure with Web Forms vs Blazor syntax comparisons, migration guide templates, sample page creation in AfterBlazorServerSide with demo and source code sections, NavMenu.razor and ComponentList.razor updates, and README linking. Use when documenting a new or existing BWFC component, creating sample pages with escaped code blocks, updating mkdocs.yml navigation, or following the complete documentation workflow from docs to samples to README.

Work with the QStash TypeScript/JavaScript SDK for serverless messaging, scheduling. Use when publishing messages to HTTP endpoints, creating schedules, managing queues, verifying incoming messages and other QStash features in serverless environments.

Lightweight guidance for using the Upstash Redis RateLimit TypeScript/JavaScript SDK, including setup steps, basic usage, and pointers to advanced algorithm, features, pricing, and traffic‑protection docs.

Git-branchless stacked diffs workflow patterns and command reference

Go testing patterns for Gentleman.Dots, including Bubbletea TUI testing. Trigger: When writing Go tests, using teatest, or adding test coverage.

Enforce separation of concerns, dependency inversion, and resilience patterns across layered and distributed architectures. Use when designing new features, evaluating module boundaries, selecting architectural patterns, or resolving scalability bottlenecks.

Enforce universal security protocols for safe, resilient software. Use when implementing authentication, encryption, authorization, input validation, secret management, or any security-sensitive feature across any language or framework.

Launch and navigate the ccboard TUI/Web dashboard for Claude Code. Use when monitoring token usage, tracking costs, browsing sessions, or checking MCP server status across projects.

Show ToonDex debug mode usage statistics. Tracks hook fires, index.toon reads, and effectiveness metrics.

Use when training Roboflow models or improving accuracy - covers architecture selection, model IDs, checkpoints, evaluation metrics, and the iterative improvement playbook.

Build dependency network and critical path from a matter plan. Produce an interactive Gantt, flag near-critical tasks, and run what-if cascade scenarios when delays occur — showing programme impact and drafting communications. Produces filtered workstream or jurisdiction views for local counsel. Trigger on: 'build a timeline', 'Gantt chart', 'critical path', 'what if X is delayed', 'what moves if', 'schedule impact', 'how does this affect the programme', 'when do we finish', 'can we still close on time', 'if we miss this deadline', 'run a what-if', 'visualise the plan', 'Germany timeline', 'what does the Employment workstream look like', 'timeline for local counsel', 'just show me the [workstream] tasks'.

PyTorch-native Graph Neural Network framework for molecules and proteins. Suitable for building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reasoning. Best for custom model development, protein property prediction, and retrosynthesis. If you need pretrained models and diverse feature extractors, use deepchem; if you need benchmark datasets, use pytdc.