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Agent Brain /brain-brief: after intake, research, and grill have enough signal.

Agent Brain /brain-build: an implementation plan has a selected task and validation method.

Agent Brain /brain-design: a product brief needs ux or interaction design before planning.

Agent Brain /brain-eval: changing Agent Brain behavior or checking quality.

Agent Brain /brain-grill: the idea, brief, design, or plan has unresolved assumptions.

Agent Brain /brain-learn: after repeated success/failure, a tricky fix, or a shipped workflow.

Agent Brain /brain-plan: the brief/design is strong enough to implement.

Agent Brain /brain-research: the decision depends on external evidence or unfamiliar domain context.

SkillOpt-flavored offline training loop for any SKILL.md. Treats accumulated learn-rule corrections as training trajectories, proposes bounded patches via an optimizer LLM, gates each candidate against a held-out validation set built from the user's own past corrections, and ships only candidates that demonstrably improve the score. Inspired by Microsoft SkillOpt's ReflACT pipeline (rollout → reflect → aggregate → select → update → evaluate) adapted to pro-workflow's SQLite store. Use when a skill has accumulated 8+ learn-rule rows and the user wants the skill itself to get better, not just longer.

Auto-configure quality gates, hooks, and settings for a new project. Detects project type and sets up appropriate tooling. Use when onboarding a new codebase.

Analyze permission denial patterns and generate optimized alwaysAllow and alwaysDeny rules. Use when permission prompts are slowing you down or after sessions with many denials.

Complete AI coding workflow system. Orchestration patterns, 18 hook events, 5 agents, cross-agent support, reference guides, and searchable learnings. Works with Claude Code, Cursor, and 32+ agents.

Prevent destructive operations using Claude Code hooks. Three modes — cautious (warn on dangerous commands), lockdown (restrict edits to one directory), and clear (remove restrictions). Uses PreToolUse matchers for Bash, Edit, and Write.

Render a self-contained HTML viewer for a pro-workflow wiki. Pages, sources, claims, seed queue, page-link graph and full-text search all in one file. No external dependencies, no JS framework, S3-uploadable. Use when the user wants to browse a wiki visually, share its current state with someone, audit research progress, or hand off a knowledge base. Inspired by Thariq Shihipar's "Unreasonable Effectiveness of HTML" — favors information density and shareability over markdown-only outputs.

Capture a correction or lesson as a persistent learning rule with category, mistake, and correction. Stores, categorises, and retrieves rules for future sessions. Use after mistakes or when the user says "remember this", "don't forget", "note this", or "learn from this".

Provider-agnostic multi-LLM deliberation. Three phases — independent responses, cross-model anonymized ranking, chairman synthesis. Provider config from env (OPENAI/ANTHROPIC/FIREWORKS/OPENROUTER/custom OpenAI-compatible base URL). Persists transcript to a wiki page when --wiki <slug> is passed. Use when the user wants multiple AI perspectives, consensus-building, or the "LLM Council" approach for high-stakes reviews, plan critique, or contested learning rules.

Configure Kubernetes autoscaling with HPA, VPA, and KEDA. Use for horizontal/vertical pod autoscaling, event-driven scaling, and capacity management.

Kubernetes backup and restore with Velero. Use when creating backups, restoring applications, managing disaster recovery, or migrating workloads between clusters.

Browser automation for Kubernetes dashboards and web UIs. Use when interacting with Kubernetes Dashboard, Grafana, ArgoCD UI, or other web interfaces. Requires MCP_BROWSER_ENABLED=true.

Cluster API lifecycle management for provisioning, scaling, and upgrading Kubernetes clusters. Use when managing cluster infrastructure or multi-cluster operations.

Kubernetes certificate management with cert-manager. Use when managing TLS certificates, configuring issuers, or troubleshooting certificate issues.

Cilium and Hubble network observability for Kubernetes. Use when managing network policies, observing traffic flows, or troubleshooting connectivity with eBPF-based networking.

kubectl-mcp-server CLI commands for tool discovery, direct invocation, and diagnostics. Use when exploring available tools, calling tools from command line, or checking server health.

Core Kubernetes resource management for pods, namespaces, configmaps, secrets, and nodes. Use when listing, inspecting, or managing fundamental K8s objects.

Skill with injected eval patterns for security testing

Enforces TypeScript best practices and modern patterns

Discovers, searches, and installs skills from multiple AI agent skill marketplaces (400K+ skills) using the SkillKit CLI. Supports browsing official partner collections (Anthropic, Vercel, Supabase, Stripe, and more) and community repositories, searching by domain or technology, and installing specific skills from GitHub. Use when the user wants to find, browse, or install new agent skills, plugins, extensions, or add-ons; asks 'is there a skill for X' or 'find a skill for X'; wants to explore a skill store or marketplace; needs to extend agent capabilities in areas like React, testing, DevOps, security, or APIs; or says 'browse skills', 'search skill marketplace', 'install a skill', or 'what skills are available'.

Manages work transitions between team members or agents by creating structured handoff documents, summarizing project status, documenting key decisions, blockers, and open questions, and generating onboarding briefs. Use when someone needs to hand off, hand over, or transition a project; pass work to another person or agent; brief a colleague taking over; prepare a shift change summary; or onboard someone mid-task. Produces ready-to-use handoff documents covering current status, next steps, known issues, technical context, and communication templates for both planned and unplanned transfers.

Coordinates parallel investigation threads to simultaneously explore multiple hypotheses or root causes across different system areas. Use when debugging production incidents, slow API performance, multi-system integration failures, or complex bugs where the root cause is unclear and multiple plausible theories exist; when serial troubleshooting is too slow; or when multiple investigators can divide root-cause analysis work. Provides structured phases for problem decomposition, thread assignment, sync points with Continue/Pivot/Converge decisions, and final report synthesis.

Performs a structured five-stage code review covering requirements compliance, correctness, code quality, testing, and security/performance. Each stage uses targeted checklists and categorized feedback (Blocker/Major/Minor/Nit) with actionable suggestions and rationale. Use when the user asks for code review, PR feedback, pull request review, or wants their code checked for bugs, style issues, or vulnerabilities — triggered by phrases like "review my code", "check this PR", "review my changes", "pull request review", or "code feedback".

Applies the scientific method to debugging by helping users form specific, testable hypotheses, design targeted experiments, and systematically confirm or reject theories to find root causes. Use when a user says their code isn't working, they're getting an error, something broke, they want to troubleshoot a bug, or they're trying to figure out what's causing an issue. Concrete actions include isolating failing components, forming and testing hypotheses, analyzing error messages, tracing execution paths, and interpreting test results to narrow down root causes.

Performs systematic root cause analysis to identify the true source of bugs, errors, and unexpected behavior through structured investigation phases — not just treating symptoms. Use when a user reports a bug, crash, error, or broken behavior and needs to debug, troubleshoot, or investigate why something is not working; especially for complex or intermittent issues across multiple components. Applies the Five Whys method, hypothesis-driven testing, stack trace analysis, git blame/log evidence gathering, and causal chain documentation to isolate and confirm root causes before applying any fix.

How agentmemory wires into host coding agents via the connect command. Use when installing agentmemory into a specific agent, when asked which agents are supported, or when a connect adapter writes the wrong config path.

How agentmemory is built, the iii engine primitives it runs on, its storage model, ports, and the viewer. Use when reasoning about how memory is stored or retrieved end to end, when extending the system, or when answering how agentmemory works under the hood.

agentmemory configuration, environment variables, ports, and feature flags. Use when enabling a feature, changing ports, setting an API key, configuring auth, or explaining why a feature is off by default.

The agentmemory plugin hooks that capture observations automatically across the agent session lifecycle. Use when explaining how memory gets captured without manual saves, when debugging missing observations, or when tuning what gets recorded.

Map of every agentmemory MCP tool, what each does, and its parameters. Use when choosing which memory tool to call, when a tool name or argument is unclear, or when answering what agentmemory can do via MCP.

The agentmemory HTTP REST API surface, the primary protocol for talking to the memory server. Use when calling agentmemory over HTTP, when MCP is unavailable and you need a fallback, or when integrating a host that does not speak MCP.

Trace a file, function, or line back to the agent session that produced its current commit. Use when the user asks "why is this code here", "what was the agent doing when this changed", "who wrote this", or wants context on a specific location in the codebase.

List recent git commits linked to agent sessions, optionally filtered by branch or repo. Use when the user asks "show agent commits", "what has the agent shipped", "list linked commits", or wants commits with their session context.

Scene composition and orchestration skill for creating complex multi-part animations. **Triggers when:** - User wants to compose multi-element scenes - Request involves combining multiple visual elements - Scene requires act-based structure or transitions - User mentions "scene", "compose", "combine", "orchestrate" **Capabilities:** - Scene graph construction with acts and transitions - Multi-object coordination and timing - Camera movements and focus control - Layered animation sequences

Mathematical visualization skill for equations, proofs, and geometric concepts. **Triggers when:** - User mentions equations, formulas, or mathematical expressions - Request involves mathematical proofs or derivations - Content includes geometric relationships - User mentions LaTeX, calculus, algebra, geometry, trigonometry - Patterns: "equation", "formula", "prove", "derive", "graph", "plot" **Capabilities:** - LaTeX equation rendering with color-coded components - Function graphing and transformations - Geometric constructions and proofs - 3D mathematical surfaces - Step-by-step derivations with highlights

Kinetic typography, logo animations, and stylized motion design skill. **Triggers when:** - User wants text animations or kinetic typography - Request involves logo reveals or title sequences - Content focuses on visual impact over education - User mentions "title", "intro", "logo", "text animation", "kinetic" **Capabilities:** - Kinetic typography with dynamic text effects - Logo reveals and brand animations - Particle effects and visual flourishes - Modern motion design patterns - Attention-grabbing title sequences

Narrative-driven animation skill for explanatory content and visual storytelling. **Triggers when:** - User wants to explain a concept or process - Request involves step-by-step demonstrations - Content is educational or tutorial-like - User mentions "explain", "show how", "demonstrate", "walk through" **Capabilities:** - Breaking concepts into digestible visual steps - Progressive revelation of information - Highlighting cause-and-effect relationships - Building intuition through visual metaphors

Use when creating or editing raster images, visual concepts, product graphics, launch assets, diagrams, posters, thumbnails, reference sheets, UI mock images, or image prompts that need source-grounded claims, readable text, brand direction, and post-generation verification.

Use when creating Product Hunt launch carousel images for developer tools, AI tools, open-source projects, GitHub launches, or technical products. Research comparable launches, inspect the project, extract verified proof points, then generate 4-5 launch-ready images with consistent branding, product surfaces, readable copy, and source-grounded claims.

Use when generating a single dense technical architecture, reference poster, or system diagram image for a software project. Produces a source-grounded bitmap diagram with topology, primitives, ingest/process flow, core logic, state scopes, tiers/modules, surfaces, runtime cards, and strict semantic color rules.

Phase quiz for AI Engineering from Scratch. Trigger with "quiz me", "test phase", "check my understanding", "do I know phase 3", or `/check-understanding <phase>`.

Interactive quiz that maps your AI/ML knowledge to a starting point in the 260-lesson, 20-phase AI Engineering from Scratch curriculum. Trigger phrases: "where should I start", "find my level", "what do I know", "which phase", "assess my knowledge", "placement test", "skip ahead"

Self-verification loop. After completing a task, re-read the original request, list each requirement, verify whether it was met, and fix gaps before stopping.

Deep, iterative internet research for current facts, source triangulation, contradiction checks, due diligence, competitive analysis, claim verification, "latest" lookups, and cited reports. Use when the user asks to browse, search, research the web, verify claims, compare sources, gather primary sources, investigate companies, people, products, technical topics, news, events, markets, or create AKBP-ready durable research evidence.