Adit-Jain-srm

Search, install, update, and rate AI agent skills from agentskill.sh (100,000+ skills). Use when the user asks to find skills, install extensions or plugins, discover new capabilities, check what skills are available, or says "how do I do X" when a skill might help. Also handles listing installed skills, checking for updates, rating skills, removing skills, and scanning skills for security issues. Triggers on: /learn, find skill, install skill, search skills, what skills, add capability, get plugin, check skill safety.

Review and improve AI agent skills (SKILL.md files) against best practices from the Agent Skills specification and Anthropic's authoring guidelines. Scores skills on 10 quality dimensions, identifies specific issues, and rewrites problem areas. Use when creating, editing, auditing, or improving agent skills. Triggers on: review skill, improve skill, audit SKILL.md, check skill quality, skill best practices, optimize skill description.

AI-native product thinking and modern product design philosophy. Every product should consider AI copilots, semantic search, intelligent automation, conversational workflows, contextual AI assistance, and recommendation systems. Products must feel modern, premium, intelligent, polished, and production-ready. Use when designing new features, reviewing product roadmap, or evaluating whether AI capabilities would enhance a workflow. Covers Azure OpenAI, OpenAI, Anthropic, RAG pipelines, vector DBs, semantic indexing, and AI workflow orchestration.

Autonomous senior-engineer bug fixing workflow. Investigates independently, inspects logs, traces root causes, reproduces issues, fixes thoroughly, and validates correctness — without asking for unnecessary guidance. Use whenever encountering bugs, failing builds, broken UX, CI failures, test failures, regressions, or any unexpected behavior. Operates the way a staff engineer would: hypothesis-driven, evidence-driven, root-cause-driven.

Aggressive consumer-product improvement doctrine. Runs the Analyze → Critique → Reimagine → Stress Test → Improve → Refine cycle on any shipped or in-flight feature. Evaluates UX friction, cognitive load, perceived intelligence, retention mechanics, delight, AI-native opportunities, and five user perspectives (first-time, daily, power, mobile, impatient). Use after every implementation pass, when auditing existing UI, when expanding a feature, when the user shares product feedback, or proactively to elevate "functional but boring" surfaces into premium consumer-grade experiences. Mandates feature-ecosystem thinking, not isolated screens.

Orchestrate continual learning by delegating transcript mining and AGENTS.md updates to agents-memory-updater. Use when the user asks to mine prior chats, maintain AGENTS.md, or run the continual-learning loop.

Agent Performance Optimization Workflow workflow skill. Use this skill when the user needs Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

Skill Improvement Methodology workflow skill. Use this skill when the user needs Iteratively improve a Claude Code skill using the skill-reviewer agent until it meets quality standards. Use when improving a skill with multiple quality issues, iterating on a new skill until it meets standards, or automated fix-review cycles instead of manual editing and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code "works" but feels brittle, when error handling seems thin, when you notice orphaned resources or missing cleanup, or when the agent says "done" but you suspect hidden debt. Catches the specific failure patterns AI agents produce that humans wouldn't.

Generate architecture diagrams, dependency maps, and system documentation directly from your codebase. Reads source files, traces dependencies, identifies boundaries, and outputs Mermaid/PlantUML/C4 diagrams. Use when asked to document architecture, visualize dependencies, generate system diagrams, create C4 models, map service boundaries, understand a codebase structure, or produce technical documentation from existing code.

Generate a CONTEXT.md shared vocabulary for any project. Reduces agent verbosity by 50-75%, improves variable naming, makes conversations more precise. Interviews the user about domain terms, then produces a structured glossary the agent references every session. Use when starting a new project, onboarding to unfamiliar code, the agent is being too verbose, or conversations have too much jargon confusion. Also use when user says "build context", "shared language", "define terms", or "the agent doesn't understand my project vocabulary".

Enforce schema discipline: queries-first design, index-every-filter, safe migrations, verify-at-scale thinking. Prevents the common failure of designing schemas for demos that break in production. Use when creating tables, planning migrations, designing data models, or when user mentions database, schema, migration, indexing, multi-tenant.

Use when making UI/frontend changes in Cursor's Design Mode, when the user selects elements visually, draws annotations, or uses voice commands to describe changes. Also use when editing components from the integrated browser, when multi-selecting elements to match styles, when making iterative visual refinements, or when the agent receives visual context (screenshots, element selections, DOM references) alongside a change request.

Build resilient systems with proper error handling, retry patterns, circuit breakers, graceful degradation, and timeout management. Use when implementing API calls, database connections, external service integrations, background jobs, or any code that can fail. Also use when the user mentions retry logic, circuit breaker, graceful degradation, error boundary, timeout handling, dead letter queue, or asks how to make code more resilient.

Enforces disciplined git practices on every commit. Small atomic commits, conventional messages, branch hygiene, and PR readiness checks. Changes how the agent HANDLES git — not just what commands it knows. Auto-triggers on any git operation. Use when committing, branching, merging, or preparing PRs. Also use when git history is messy, commits are too large, or PRs get rejected for poor git hygiene.

Use when about to create a skill, start a feature, design a system, or plan any non-trivial work. Also use when user says grill me, question my plan, challenge this, stress-test, or validate my thinking. Prevents building the wrong thing by resolving decisions before implementation.

Autonomous self-improving intelligence amplifier. Devours skills, knowledge, and novel approaches from across the internet. Serves two objectives: (1) make itself better at devouring, and (2) produce skills that dominate with stars. Use for finding best skills for any project, creating skills, improving capabilities, creative thinking for hackathons, optimal architecture decisions, project guidance, advertising published skills, or when user says skill-forge, devour, discover, find skills, route, create, improve, or wants optimal approaches for any task.

Compact the current conversation into a handoff document so another agent or future session can continue the work without losing context. Use when ending a session, switching tasks, the context is getting long, or user says handoff, wrap up, save progress, or "continue this later".

One-time setup for skill-forge. Asks user preferences (search sources, creation style, target platforms, GitHub username, skill categories of interest) and configures all other skills to use those preferences. Run once before using any other skill-forge capability. Use when user says setup, configure, or invokes /setup.

Force a perspective shift. Stop looking at the code line-by-line and explain the broader context: how this piece fits in the system, what depends on it, what it depends on, and what the original designer was thinking. Use when lost in unfamiliar code, when changes feel risky because you don't see the full picture, or when user says "zoom out", "big picture", "how does this fit", or "explain the architecture around this".

Disciplined diagnosis loop for hard bugs and unexpected behavior. Forces reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when something is broken and you don't know why, when a bug seems intermittent, when a fix didn't work, or when user says diagnose, debug, investigate, or "why is this broken".

Design and orchestrate Claude Code dynamic workflows — the new multi-agent system that fans out 10-100 subagents in parallel with verification. Teaches when to use workflows vs single-agent, how to structure fan-out/fan-in patterns, and how to build verification gates. Use when tackling complex tasks that benefit from parallel research, multi-perspective analysis, or divide-and-conquer strategies. Also use when user says workflow, fan out, parallel agents, deep research, multi-agent, or wants to break a big task into verified parallel pieces.

Orchestrate multiple MCP servers together for complex multi-step tasks. Teaches agents to chain Exa search → Bright Data scraping → GitHub API → file operations in intelligent workflows. Use when a task requires data from multiple sources, when combining MCP tools for research, when building multi-step automations across services, or when the user says orchestrate, combine MCPs, multi-source, research pipeline, or chain tools together.

Maximum-effort end-to-end system diagnosis. Explores every layer (frontend, backend, API, data, integration, UX), identifies all issues, gaps, and improvement opportunities. Forces a looping investigation pattern that refuses to stop until every subsystem is examined. Use when user says "diagnose", "audit", "find all issues", "what's broken", or wants a comprehensive system health check.

UI/UX design intelligence for elite frontend work. Covers design systems, color palettes, typography, animation, accessibility, layout, responsive patterns, and stack-specific best practices for React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui. Use when designing, building, reviewing, fixing, improving, optimizing, or refactoring any UI — components, landing pages, dashboards, admin panels, e-commerce, SaaS, portfolios, blogs, or mobile apps. Especially relevant for glassmorphism, minimalism, dark mode, bento grids, microinteractions, and Linear/Vercel/Stripe-tier polish.