
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Reduce complexity by revealing information progressively. Use when designing onboarding, complex forms, feature-rich interfaces, or any experience where showing everything at once would overwhelm users.
Vitest fast unit testing framework powered by Vite with Jest-compatible API. Use when writing tests, mocking, configuring coverage, or working with test filtering and fixtures.
Adversarially improves existing agent skill packages by stress-testing workflow design, flow-diagram coherence, personality fit, subagent necessity, and package quality before applying approved changes.
Rewrite existing Python, TypeScript/JavaScript, or Go code for strict static typing, boundary validation, and maintainable idioms while preserving behavior. Use when the user asks to harden code, remove unsafe escape hatches, add validation, or align with mypy, Pyright, tsc, go vet, or Staticcheck. Coordinates baseline mapping, strategy, approved implementation, and review through co-located subagents and just-in-time language references.
Creates reviewable atomic git commits from explicit file or folder paths after the user asks to commit. Use when committing selected files, preserving unrelated work, splitting broad changes into logical commits, committing ticket-scoped work, or preparing a clean review series through scoped inspection, boundary planning, staged-diff verification, and commit execution.
Create review-ready pull requests from the current branch with a preview-first, user-approved workflow. Use when the user asks to create, open, draft, or submit a PR, pull request, merge request, or code review request, or says their branch is ready for review.
Retrieves a Jira ticket into docs/<TICKET_KEY>.md. Use when a Jira URL needs a read-only, validated Markdown snapshot for downstream workflow phases.
Runs a structured nine-seat council deliberation on an idea, project, business, startup, goal, or objective, then returns a reasoned recommendation with the mental models exposed so the user can apply them solo next time. Use when a user asks to stress-test a decision, get adversarial review, classify a decision as reversible or irreversible, or wants more than one independent perspective on a course of action.
Adversarially improves existing agent skill packages by stress-testing workflow design, flow-diagram coherence, personality fit, subagent necessity, and package quality before applying approved changes.
Coordinates subagent-driven architecture reviews and restructuring plans. Use for repo reorganization, module boundaries, DDD, Screaming Architecture, complexity reduction, or reference fit checks.
Phase 2 of the GitHub planning workflow. Reads a GitHub issue snapshot, dispatches a plan/prioritize/validate pipeline, and writes docs/<ISSUE_SLUG>-tasks.md with branch names for every planned child issue.
Generates a resumable cold-start handoff package from an in-progress conversation, review, debugging session, or investigation. Use when the user says "create a handoff doc", "save this for later", "document what we found", "update the resumption file", or wants a fresh agent to resume without chat history.
Plans execution for one task from docs/<ISSUE_SLUG>-tasks.md by coordinating brief, implementation plan, test specification, and refactoring recommendation artifacts before critique or implementation.
Plans execution for one task from docs/<TICKET_KEY>-tasks.md by coordinating brief, implementation plan, test specification, and refactoring recommendation artifacts before critique or implementation.
Phase 2 of the Jira planning workflow. Reads a Jira ticket snapshot, dispatches a plan/prioritize/validate pipeline, and writes docs/<TICKET_KEY>-tasks.md with branch names for every planned Jira subtask.
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases.
This skill embodies the principles of "Clean Code" by Robert C. Martin (Uncle Bob). Use it to transform "code that works" into "code that is clean."
Coordinates behavior-preserving code refactors. Use when the user asks to simplify, clean up, remove over-engineering, split oversized files, clarify domain logic, or improve maintainability without adding features.
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when implementing any feature or bugfix, before writing implementation code
Use when you have a spec or requirements for a multi-step task, before touching code
Assess review comments received on a pull request, decide whether to accept, modify, or push back, draft evidence-backed replies for existing GitHub review-comment threads, write a local assessment file, and keep posting confirmation-gated. Use when a user asks to review PR feedback, assess comments received on a PR, draft replies to PR review comments, decide how to address reviewer feedback, or summarize actions from PR comments.
Review pull requests through a subagent-driven workflow that gathers PR context, finds grounded defects, drafts GitHub line comments with suggestion blocks, verifies claims, writes a findings-first review file, and optionally posts only after explicit confirmation. Use when a user asks to review a PR, audit a pull request, prepare review comments, request changes, draft GitHub review feedback, or write a PR review to a file.
Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
Implement secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common API vulnerabilities
Review one pull request through a standalone, progressively disclosed workflow. Use when the user asks to review a PR, audit a pull request, prepare GitHub review comments, draft request-changes feedback, write a PR review file, or optionally post approved review comments. This skill handles exactly one PR; ask the user to choose one PR when multiple PR URLs are supplied.
Reviewer-only refinement for Jira tickets, Jira epics, GitHub issues, and GitHub epic-style parent issues. Use when the user asks to triage, refine, assess readiness, review acceptance criteria, find blockers, validate technical claims, suggest splits, recommend subtasks, or draft/post the single allowed refinement comment while leaving tracker metadata, issue content, and existing comments unchanged.
Validates answers that depend on current external facts, including prices, versions, policies, rankings, recommendations, documentation, and availability. Use when the user asks for current, latest, verified, fact-checked, or up-to-date answers. Coordinates recency-checker and claim-verifier subagents to produce a current, qualified final answer.
Executes exactly one planned Jira workflow task after critique approval. Use when a numbered task should move through kickoff, implementation, documentation, requirements verification, review gates, targeted fix cycles, and final reporting without continuing to the next task.
Audits an implementation plan for requirements traceability, avoidable complexity, risky assumptions, and evidence gaps. Use when reviewing an AI-generated or human-authored plan, design proposal, implementation outline, task breakdown, or architecture plan and the user wants a standalone audit report without overwriting the source plan.
Improve existing test suites into minimal, high-signal behavior-focused harnesses. Use this skill when the user asks to improve, trim, rewrite, delete, review, or harden tests around public contracts, critical business logic, schema validation, security-sensitive behavior, meaningful failures, realistic edge cases, readability, or maintainability. Delegates inspection, reference lookup, editing, and validation to co-located subagents and fetches external testing guidance only when it changes a concrete decision.
Assess and respond to pull request review comments through a progressive-disclosure, subagent-driven workflow. Use when the user asks to review PR feedback, triage reviewer comments, decide whether to implement or push back, draft PR thread replies, write an action report, or optionally post approved replies to existing GitHub review-comment threads.
Converts repeatable workflows into standalone, progressively disclosed agent skills with co-located subagents and references. Use when the user asks to make a skill, turn a process into an agent, automate a workflow, create slash-command-style workflows, split a procedure into skills/subagents, or improve an existing skill definition for Claude Code, Cursor, OpenCode, or Agent Skills-compatible runtimes.
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.
GitHub CLI (gh) comprehensive reference for repositories, issues, pull requests, Actions, projects, releases, gists, codespaces, organizations, extensions, and all GitHub operations from the command line.
Executes exactly one planned GitHub workflow task after critique approval. Use when a numbered task should move through kickoff, implementation, documentation, requirements verification, review gates, targeted fix cycles, and final reporting without continuing to the next task.
Create or refine Markdown plus Mermaid flow diagrams for AI-agent workflows. Use when the user asks for a process flow, workflow diagram, Mermaid flowchart, agent operating procedure, human-in-the-loop gate map, or refinement of an existing flow or process description.
Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
Reviews and tailors a software engineer CV or resume against a job posting. Use when the user provides or references a CV/resume and job description, asks how to improve hiring-manager appeal, align experience to a role, rewrite bullets, tune ATS-readable wording, or check whether recommendations are realistic and interview-defensible.
Retrieves a GitHub issue into docs/<ISSUE_SLUG>.md. Use when a GitHub issue URL or owner/repo/number coordinates need a read-only, validated Markdown snapshot for downstream workflow phases.
Creates or reconciles Jira subtasks for an approved Phase 4 task plan. Use after docs/<TICKET_KEY>-tasks.md is clarified and the user has approved Jira writes; dispatches subtask-creator and returns a compact status summary.
Coordinate an end-to-end Jira ticket workflow from ticket fetch through per-task implementation. Use this skill when the user provides a Jira URL, says "work on ticket PROJECT-123", "resume PROJECT-123", "continue this Jira ticket", "start the Jira workflow", or asks for status on a ticket without naming a specific phase. This top-level coordinator keeps SKILL.md as a routing layer, loads bundled references just in time, and dispatches execution-heavy work to downstream skills or co-located utility subagents.
Coordinate an end-to-end GitHub issue workflow from issue fetch through per-task implementation. Use this skill when the user provides a GitHub issue URL, says "work on issue owner/repo#123", "resume <issue-slug>", "continue this GitHub issue", "start the GitHub workflow", or asks for status on an issue without naming a specific phase. This top-level coordinator keeps SKILL.md as a routing layer, loads bundled references just in time, and dispatches execution-heavy work to downstream skills or co-located utility subagents. Primary GitHub transport for delegated work is gh (GitHub CLI).
Use when executing implementation plans with independent tasks in the current session
Creates or reconciles GitHub child task issues for an approved Phase 4 task plan. Use after docs/<ISSUE_SLUG>-tasks.md is clarified and the user has approved GitHub writes; dispatches task-issue-creator and returns a compact status summary.
Convert prose prompts into compact, structured XML prompts through staged subagent passes. Use when a user asks to structure, harden, formalize, debug, or convert a prompt; mentions XML tags, agent drift, ambiguity, hidden assumptions, success criteria, anti-patterns, autonomous prompts, or prompt suites; or provides natural-language instructions that need to become a reliable agent contract.
Runs the conversational clarification layer for workflow orchestration. Use for plan-wide upfront clarification or task-level pre-execution critique while delegating artifact analysis, manifest assembly, and file updates to bundled subagents.
Produces a recent project state snapshot from Git evidence. Use when a user asks what changed recently, wants staged or unstaged work explained, needs a branch handoff, wants risks in rushed or AI-assisted changes, or needs practical next steps before merging or continuing work in a repository.