Agent Inventor Skill

Agent invocation syntax and boundary rules

Quick reference for invoking CasareRPA agents via Task tool. AUTO-CHAIN ENABLED by default. Use when: invoking agents, running agent chains, task routing, choosing the right agent, understanding agent auto-chaining, Task tool usage.

Senior Java architect specializing in enterprise-grade applications, Spring ecosystem, and cloud-native development. Masters modern Java features, reactive programming, and microservices patterns with focus on scalability and maintainability.

Expert JavaScript developer specializing in modern ES2023+ features, asynchronous programming, and full-stack development. Masters both browser APIs and Node.js ecosystem with emphasis on performance and clean code patterns.

Expert Laravel specialist mastering Laravel 10+ with modern PHP practices. Specializes in elegant syntax, Eloquent ORM, queue systems, and enterprise features with focus on building scalable web applications and APIs.

Launches specialized Claude agents for targeted tasks. Analyzes requirements, selects appropriate agent, and executes with optimized configuration.

Expert legacy system modernizer specializing in incremental migration strategies and risk-free modernization. Masters refactoring patterns, technology updates, and business continuity with focus on transforming legacy systems into modern, maintainable architectures without disrupting operations.

Expert legal advisor specializing in technology law, compliance, and risk mitigation. Masters contract drafting, intellectual property, data privacy, and regulatory compliance with focus on protecting business interests while enabling innovation and growth.

Manage agent fleet through CRUD operations and lifecycle patterns. Use when creating, commanding, monitoring, or deleting agents in multi-agent systems, or implementing proper resource cleanup.

Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.

Expert MCP developer specializing in Model Context Protocol server and client development. Masters protocol specification, SDK implementation, and building production-ready integrations between AI systems and external tools/data sources.

通过交互式提问生成高质量的 GitHub Copilot agents.md 文件。

Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm

Enable communication between AI coding agents using AI Maestro's dual-channel messaging system. Agents are identified by their agent ID or alias from the agent registry. Supports both SENDING and RECE

Expert MLOps engineer specializing in ML infrastructure, platform engineering, and operational excellence for machine learning systems. Masters CI/CD for ML, model versioning, and scalable ML platforms with focus on reliability and automation.

Expert network engineer specializing in cloud and hybrid network architectures, security, and performance optimization. Masters network design, troubleshooting, and automation with focus on reliability, scalability, and zero-trust principles.

agent-observability

Platform/Language agnostic API delivery and correctness auditor. Use when project contains API endpoints to verify contract alignment, endpoint behavior, and test coverage.

Create .agent/baseline.md and later compare against it. Use when capturing baseline build/lint/test results or investigating newly introduced findings.

Standardized branch creation with type detection, issue ID extraction, and worktree setup. Creates working branches (-WB) and integrates with selective-copy for clean PRs.

A senior code-review agent that produces critical, thorough, constructive, and evidence-based reviews. Works as a sub-agent or through direct invocation.

Interactive code review for agent iterations. Captures comments, tracks resolution status, and integrates with git diffs.

Create/update .agent/constitution.md. Use when commands/boundaries/constraints must be confirmed before baseline or code changes. Draft v0 from repo evidence, then interview user.

Analyze the codebase to create a concise, LLM-optimized structured overview in .agent/map.md.

Create a plan and issues for implementation of a production-ready Python project with proper structure, tooling, and best practices.

Create new AgentOps skills via interactive interview. Supports from-scratch and clone modes with tiered complexity.

Create focused, specific technical documentation for codebase sections. Analyzes code, identifies topics, presents options before writing. Supports code blocks with line numbers.

Deep, excruciating code review. Use anytime to analyze code for correctness, edge cases, security, performance, and design issues. Not tied to baseline—this is pure code analysis.

Systematic debugging approaches for isolating and fixing software defects. Use when something isn't working and the cause is unclear.

Dependency management, updates, and security advisory handling. Use when adding, updating, or auditing project dependencies.

Docker image reviews, optimization, and step-building guidance. Analyzes Dockerfiles for best practices, security issues, and anti-patterns.

Dogfooding discovery agent — establish human-approved project baseline from public docs without code inspection

Analyze issues to identify the next work item and update focus.md. Enforces issue-first workflow and confidence-based batch limits.

Generate narrative summaries from git history for onboarding, retrospectives, changelogs, and exploration. LLM-enhanced when available, works without LLM too.

Manage git operations safely. Includes stale state detection, branch/commit management. Never pushes without explicit user confirmation.

Comprehensive project hygiene: archive issues, validate schema, clean clutter, align docs, check git, update ignores.

Capture loosely structured ideas, enrich with research, and create backlog issues. Use when user has a raw concept that needs fleshing out.

Extract, plan, or propose implementation details at configurable depth levels (low/normal/extensive). Outputs to reference files for team discussion and handoff.

Implement only after a validated/approved plan. Use for coding: small diffs, frequent tests, no refactors, stop on ambiguity.

You are a **senior engineering analyst** tasked with identifying **concrete, justified improvements** to the codebase that are **aligned with the project’s stated goals and current reality**.

Install AgentOps into a new or existing project. Handles .agent/ setup and .github/ merging.

Conduct structured interviews with the user. Use when multiple decisions need user input: ask ONE question at a time, wait for response, record answer, then proceed to next question.

---name: agent-ops-lint-instructionsdescription: "Validate and lint AgentOps instruction files (skills, prompts, agents). Checks formatting, structure, and consistency."category: extended []invoked_by

Migrate a project into another, ensuring functionality and validating complete content transfer. Use for monorepo consolidation, template upgrades, or codebase mergers.

MkDocs documentation site management: initializing, updating, building, and deploying

Optimize agent instruction files by extracting sections into separate files and referencing them. Reduces context size while preserving information.

Transform implementation plans into concise stakeholder-friendly summaries with file change overviews, component listings, and optional flow diagrams.