social-content-studio

The Ultimate Senior Fixer. Combines planning, specification, and coding into a single, high-speed execution mode for one-off tasks, ad-hoc fixes, and minor refactors. Bypasses standard SDLC paperwork while strictly enforcing Karpathy-level meticulousness and Ponytail-level simplicity. Trigger via /code-janitor or when the user asks for a quick fix, cleanup, or fast minor feature outside the SDLC process.

An advanced, autonomous AI agent skill designed to execute complex, multi-step, and long-horizon tasks with high reliability and minimal human interruption.

Grill the user relentlessly about a plan or design. Use when the user wants to stress-test a plan before building, or uses any 'grill' trigger phrases.

AI-Guided Learning mentor. Guides the user step-by-step to build and learn a new technology without writing the final code for them.

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.

Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.

Omni-expert principal software architect. Triggers on requests for app development, coding, refactoring, or architectural design. Enforces clean code, clean architecture, deep reasoning, mandatory testing, and strict anti-ambiguity protocols.

Applies the "lazy senior developer" mindset. Use this skill whenever generating, modifying, reviewing code, or fixing bugs to prioritize code reuse, minimalism, YAGNI principles, and root-cause fixes. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path". Supports intensity levels: lite, full (default), ultra. Also includes sub-modes for over-engineering review (ponytail-review), repo-wide audit (ponytail-audit), and debt tracking (ponytail-debt).

Performs consistency and traceability audits across documents (PRD vs Spec vs Plan) to detect missing coverage and scope creep.

Workflow for analyzing bug reports, tracing root causes, and generating structured bug-fix implementation plans with rollback strategies.

Helps interrogate Product Requirements (PRD), Technical Specifications, and Implementation Plans to find ambiguities, missing edge cases, and hidden assumptions.

Language-agnostic workflow for code reviews and security audits using a Two-Axis (Standards vs Spec) approach against Clean Code/SOLID principles, generating formal refactoring plans.

Generates or updates highly detailed, machine-readable technical specification documents in the /spec/ directory.

Workflow to generate a comprehensive Product Requirements Document (PRD) detailing user stories, acceptance criteria, technical considerations, and metrics.

Systematic codebase exploration, architectural critique, and generation of Project Discovery Drafts for SDLC Phase 0.

Workflow for auditing, designing, and writing structured documentation based on the Diátaxis Framework (Tutorials, How-to, Reference, Explanation).

Initializes the Awesome Copilot ID SDLC architecture, AGENTS.md, and rules in the current project.

Scans, analyzes, and documents the existing repository architecture, directories, and file purposes into docs/ARCHITECTURE.md.

Generates formal, structured, and executable implementation plan documents based on specifications.

Phase 6: Coding & Execution. God-Tier Autonomous Engineer implementing code strictly based on approved /spec/ and /plan/.