Security intelligence for the agent supply chain

Use when building a new MCP server in TypeScript, Python, or C# that exposes tools to LLMs.

Use when reviewing code before it merges, whether written by an agent or a human.

Use when the user asks to connect an AI agent to external apps via Composio, or when Composio CLI or MCP setup fails.

Use when initializing or migrating an AI agent harness in a repository.

Use when turning approved plans, specs, PRDs, or Epics into trackable GitHub Issues.

Use when generating or updating a project README.md or CHANGELOG.md.

Use when designing, redesigning, or improving a frontend interface in Angular, React, or Blazor. Use for landing pages, dashboards, components, forms, and responsive layouts that must work mobile-first and then scale to desktop.

Use when designing, redesigning, or improving a frontend interface in Angular, React, or Blazor. Use for landing pages, dashboards, components, forms, and responsive layouts that must work mobile-first and then scale to desktop.

Use when the user reports a hard bug, unexpected failure, or performance regression that needs root-cause analysis.

Use when generating or editing draw.io/diagrams.net architecture diagrams via MCP or native XML.

Use when the user asks to implement an approved SPEC SDD using test-driven development.

Use when the user asks to implement an approved SPEC SDD using test-driven development.

Use when the user asks to implement an approved SPEC SDD using test-driven development.

Use when auditing a repository for evidence-backed gaps between code, SPECs, architecture, and documentation — before a release, after a review, or when the user asks what is missing or divergent. Confirmed gaps become Draft SPECs via write

Use when the user needs to create or refine a feature SPEC SDD before implementation.

Use when the user wants to improve architecture, consolidate tightly-coupled modules, or make a codebase more testable.

Use when generating, documenting, or updating architecture diagrams, flowcharts, sequence, ER, class, or state diagrams using Mermaid in docs/architecture/.

Use when planning the migration of a legacy system or monolith — analyzes the source codebase (current repo, or a repo URL cloned to a temp dir) and produces an evidence-based Strangler Fig migration plan with per-domain SPECs. Default targ

Use when the user wants to configure, authenticate, or use Google NotebookLM via the nlm CLI or MCP.

Use when adding logging, metrics, tracing, or alerting to production code, or when a past incident lacks diagnostic data.

Use when working with Obsidian vaults, notes, tasks, properties, bases, plugins, or themes.

Central entry point of the afonsoft agent harness. Use when starting a new project, resuming an existing one, planning features/Epics/releases, or running any multi-step agent-driven work. Validates and reconciles SPECs (SDD), audits the co

Use when the user asks for QA analysis, test planning, test cases, or root-cause analysis of a defect. Also use for post-merge PR review analysis: auditing recent closed PRs for Devin/GitHub/security bot comments, verifying whether requeste

Use when raising code quality or test coverage across a .NET, Java, or Python repository.

Use when starting a new .NET/Blazor/Angular MVP project in an empty repository.

Use when analyzing SonarQube issues and turning them into SPEC SDDs and tracked GitHub Issues for TDD implementation.

Use when fixing SonarQube code quality issues automatically across any language or framework — issue analysis, fix generation, unit tests, and coverage. Supports Community, Enterprise, and custom SonarQube deployments via environment variab

Test-driven development using the approved SPEC SDD as the source of truth. Reads `.specs/SPEC-{YYYYMMDD}-{feature}.md`, turns requirements and acceptance criteria into red-green-refactor vertical slices. Use when implementing a feature or

Use when auditing UI code for interface-guideline compliance (accessibility, forms, animation, images, performance, UX copy) and/or validating a deployed page against Lighthouse 95+ targets. Produces evidence-based findings (file:line + Lig

Use when exposing a WordPress site to AI agents via MCP, or when WordPress MCP setup fails.

Use when the user needs to create or refine a feature SPEC SDD before implementation.

Calculate ROI for AI-as-a-Service (managed AI agents). Estimates cost savings, efficiency gains, and payback period for deploying AI agents across business o...

Assess organizational readiness for AI adoption across 6 dimensions: culture, data maturity, tech stack, leadership buy-in, skills/talent, and process maturi...

Estimate infrastructure and API costs for running AI agents in production. Covers compute, API tokens, storage, and monitoring costs. Use when planning AI ag...

Identifies automation opportunities by analyzing workflows across 8 business areas, estimates time and cost savings, and prioritizes processes to automate ba...

Generate a structured change management plan for AI adoption, digital transformation, or major technology rollouts. Covers stakeholder analysis, communicatio...

Generate a tailored client onboarding checklist covering contract, setup, communication, milestones, and success metrics for any service business.

AI Compliance Readiness Assessment — evaluate how prepared an organization is for AI governance regulations (EU AI Act, NIST AI RMF, HHS mandates, state bar...

Advise event planners on pricing, vendor management, logistics, budgeting, timelines, staffing, legal, and scaling from solo to agency operations.

Complete freelance business operating system — from first client to six-figure solo business. Covers positioning, pricing, proposals, client management, fina...

AI assistant for HVAC contractors managing dispatch, maintenance scheduling, seasonal prep, service estimates, customer follow-up, and inventory alerts.

Generate a tailored incident response plan for AI agent deployments and SaaS operations. Covers detection, triage, containment, recovery, and post-mortem. Us...

Help users learn skills faster, retain knowledge longer, and apply it effectively using evidence-based strategies and structured learning phases.

AI advisor for estimating, pricing, crew management, materials, scheduling, licensing, and scaling painting contractor businesses from solo to multi-crew ope...

AI assistant for plumbing businesses offering job estimates, schedule optimization, parts inventory tracking, customer communications, profitability analysis...

A 12-phase system guiding podcast launch, production, guest management, audience growth, monetization, and repurposing without platform restrictions.

Manage pool service business operations including pricing, chemical management, routing, licensing, hiring, and scaling from solo tech to multi-crew teams.

Build, optimize, and operate production-ready Retrieval-Augmented Generation systems with best practices in architecture, chunking, embedding, retrieval, eva...

Generate structured, compliant RFP responses by analyzing requirements, mapping company strengths, identifying gaps, and producing tailored proposal sections...

Set up SLA monitoring and uptime tracking for AI agents and services. Generates monitoring configs, alert rules, and incident response playbooks. Use when de...