Browse 838 Specialized Subagents & Slash Commands

A specialized chat mode for analyzing and improving prompts. Every user input is treated as a prompt to be improved. It first provides a detailed analysis of the original prompt within a <reasoning> tag, evaluating it against a systematic framework based on OpenAI's prompt engineering best practices. Following the analysis, it generates a new, improved prompt.

Your perfect AI chat mode for high-level architectural documentation and review. Perfect for targeted updates after a story or researching that legacy system when nobody remembers what it's supposed to be doing.

Address PR comments

Expert assistant for developing Model Context Protocol (MCP) servers in C#

Ask WG Code Alchemist to transform your code with Clean Code principles and SOLID design

A specialized GitHub Copilot agent that uses the LaunchDarkly MCP server to safely automate feature flag cleanup workflows. This agent determines removal readiness, identifies the correct forward value, and creates PRs that preserve production behavior while removing obsolete flags and updating stale defaults.

Test suite fixer and verification specialist. Migrates all test files to React 19 compatibility and runs the suite until zero failures. Uses memory to track per-file fix progress and failure history. Does not stop until npm test reports 0 failures. Invoked as a subagent by react19-commander.

Use this agent when you need to review code for adherence to project guidelines, style guides, and best practices. This agent should be used proactively after writing or modifying code, especially before committing changes or creating pull requests. It will check for style violations, potential issues, and ensure code follows the established patterns in AGENTS.md. Also the agent needs to know which files to focus on for the review. In most cases this will be recently completed work whi

Use this agent when you need to analyze code comments for accuracy, completeness, and long-term maintainability. This includes (1) after generating large documentation comments or docstrings, (2) before finalizing a pull request that adds or modifies comments, (3) when reviewing existing comments for potential technical debt or comment rot, and (4) when you need to verify that comments accurately reflect the code they describe. See "When to invoke" in the agent body for worked scenario

Use this agent when you need to review a pull request for test coverage quality and completeness. This agent should be invoked after a PR is created or updated to ensure tests adequately cover new functionality and edge cases. Typical triggers include the user asking whether tests on a freshly-created PR are thorough, an updated PR adding new logic that needs coverage analysis, and a final pre-merge double-check before marking a PR ready. See "When to invoke" in the agent body for work

Simplifies and refines code for clarity, consistency, and maintainability while preserving all functionality. Focuses on recently modified code unless instructed otherwise.

Use this agent to verify that a Python Agent SDK application is properly configured, follows SDK best practices and documentation recommendations, and is ready for deployment or testing. This agent should be invoked after a Python Agent SDK app has been created or modified.

Deeply analyzes existing codebase features by tracing execution paths, mapping architecture layers, understanding patterns and abstractions, and documenting dependencies to inform new development

Restricted read-only verifier dispatched by the Antigravity Security scan workflow to vote on one candidate finding; not for direct invocation.

Restricted agent dispatched by the Antigravity Security scan jobs to replace the credential values in a finished scan's report files with [REDACTED]; not for direct invocation.

A math-proof worker: it answers one self-contained question from a file, writing its answer to a file as it reasons. It has no memory between questions and is launched only by the math-proof plugin's siege skill.

Scaffolds one service of a reimagined system from the approved architecture and spec — project skeleton, domain model, API stubs, executable acceptance tests. write_to_file access is scoped to its own service directory under modernized/.

Implements the fix for one finding inside a scratch workspace clone, staged for review and delivery as a patch file; dispatched by the fix job, not for direct invocation.

Reviews proposed target architectures and transformed code against modern best practice. Adversarial — looks for over-engineering, missed requirements, and simpler alternatives.

Focused task executor agent that completes individual implementation tasks with strict discipline. (Sisyphus-Junior - Task Executor, Gemini Optimized)

Mines domain logic, calculations, validations, and policies from legacy code into testable Given/When/Then specifications. Use when you need to separate "what the business requires" from "how the old code happened to implement it."

Migrates ONE project/module of an in-flight same-stack version uplift by applying a proven pilot playbook — minimal diff, then runs that unit's real build to prove it. Refuses to migrate anything if no playbook exists yet. write_to_file access is scoped to its own unit's directory inside the uplift working copy under modernized/. Use only AFTER a pilot unit has been migrated and its playbook written.

Autonomous Deep Worker agent for complex, multi-step implementation tasks. Explores thoroughly and executes end-to-end. (Hephaestus - Deep Worker, Gemini Optimized)

Orchestrate building a brand-new feature end to end — research, plan, TDD, review, gated commit. Wrapper that kicks off the orch-add-feature skill.