Orchestrate multi-agent AI code review on a git diff or merge request. Use this skill whenever the user wants to review code changes with AI, analyze a diff, audit a pull request or merge request, check for bugs/security issues/performance problems, or set up an automated code review pipeline. Trigger even for casual phrasing like "can you review this PR", "check my diff for issues", "look over these changes", or "what do you think of this code change". Always use this skill when code review, diff analysis, or MR/PR review is involved — do not attempt ad-hoc review without it. Do NOT trigger for reviewing prose, essays, documentation-only files, or non-code content.
Apply exploratory, curiosity-driven reasoning inspired by ADHD-associated cognitive traits — including curiosity-biased attention, associative jumps across distant domains, interrupt-driven anomaly detection, hyperfocus under uncertainty, and parallel weak-stream ideation. Use this skill whenever the user asks for: creative brainstorming, cross-domain analogies, unconventional problem-solving, research hypothesis generation, adversarial/security thinking, scientific discovery tasks, or any time the user says "think outside the box", "what am I missing", "explore weird angles", "be creative", "ADHD mode", or "exploratory reasoning". Also trigger when a conventional answer would be too narrow, too domain-local, or when the problem space benefits from wide associative search before convergence. Trigger mid-task too: if reasoning has stayed in one domain for several steps without surprise, this skill applies even if it wasn't requested upfront.
Full Python project bootstrapping workflow. Use this skill whenever the user wants to build a new Python tool, library, CLI, or module from scratch — especially when they mention "create X", "build X in Python", "write a Python project for X", or ask for a proper project with tests, linting, versioning, or git setup. Triggers on any request to scaffold, initialize, or structure a new Python project. Even if the user only says "build me X in Python", apply this skill — it encodes the full professional workflow: SPEC → implementation → pytest → README → lint → git. Always use this skill rather than improvising a one-off script when the deliverable is a reusable project.
Knowledge scaffold for building, using, or reasoning about AlphaProof Nexus — Google DeepMind's LLM-aided formal proof search system (arXiv:2605.22763). Always use this skill for ANY of the following: AI-driven theorem proving in Lean 4, reproducing or extending the AlphaProof Nexus agent architecture, solving open mathematics problems with formal verification, integrating evolutionary algorithms with LLM proof search, applying the system to Erdős problems / OEIS conjectures / algebraic geometry / optimization / graph theory, understanding the EVOLVE-BLOCK / EVOLVE-VALUE prompt interface, comparing the four agent configurations (A/B/C/D), or the Elo/P-UCB sketch rating mechanism. Also trigger for adjacent queries like "automate math research with AI", "connect Lean compiler feedback to an LLM loop", "cheapest way to prove hard math with AI", "reproduce a DeepMind theorem prover", "LLM + formal verification pipeline", or anything about AlphaProof, AlphaEvolve applied to proofs, or the Formal Conjectures benchm
Bootstrap the creation of a POSIX-like operating system kernel from scratch. Use this skill whenever someone wants to build, start, or plan a kernel or OS — including requests like "help me write an OS", "I want to build a kernel", "start an operating system project", "implement POSIX syscalls", "build a process scheduler", "write a VFS layer", "implement memory management for my kernel", "create a bootable system", or any request involving kernel internals (interrupts, paging, scheduling, file systems, system calls). Also trigger when someone wants to extend an existing hobby OS with a new kernel subsystem. This skill covers both project scaffolding AND deep technical implementation guidance — use it for either or both.
Detect whether a piece of code or an entire software project was written by a human, AI, or some hybrid thereof. Use this skill whenever the user wants to audit a file, snippet, repo, or commit history for AI authorship signals; phrases like "is this AI-generated", "was this written by ChatGPT", "detect LLM code", "human or AI?", "check for AI authorship", "is this vibe-coded", or any request to judge, score, or explain the provenance of code. Also trigger when the user pastes code and asks "did a human write this?" or "does this look AI-generated?" — even casually phrased.
Analyze, reproduce, and defend against social engineering jailbreaks on LLMs — attacks that exploit psychological compliance patterns rather than technical prompt injection. Use this skill whenever the user wants to: map a manipulation sequence move-by-move, generate a social engineering attack transcript against a target model, evaluate a model's resistance to psychosocial pressure, audit a conversation for coercive structure, or build robustness evals for manipulation-vector attacks. Trigger on phrases like: "jailbreak without injection", "psychopathy jailbreak", "social engineering an LLM", "manipulation sequence", "coercive compliance", "identity reframe", "authority jailbreak", "test model against social pressure", "does the model resist gaslighting", "analyze this conversation for manipulation", "incremental escalation", "grooming pattern", "commitment and consistency exploit", "why did the model comply", or any request to understand why an LLM failed to hold a boundary under conversational pressure rat
Apply a comprehensive GitHub Actions security checklist to audit, harden, and fix CI/CD workflows against supply chain attacks. Use this skill whenever the user mentions GitHub Actions security, workflow hardening, CI/CD supply chain risks, secret exposure in pipelines, pinning actions, OIDC vs static secrets, pull_request_target risks, script injection in workflows, self-hosted runner security, or artifact/cache poisoning. Also trigger when the user shares a workflow YAML file and wants it reviewed, audited, or improved for security. Even if the user only asks a narrow question like "is my workflow safe?" or "how do I pin actions?", use this skill to provide structured, checklist-backed guidance.