A CodeGuard security skill that helps AI coding agents write secure code and prevent common vulnerabilities. Use this skill when writing, reviewing, or modifying code to ensure secure-by-default practices are followed.
Guide secure migration of code from memory-unsafe languages (C, C++, Assembly) to memory-safe languages (Rust, Go, Java, C#, Swift). Use when migrating or rewriting legacy C/C++ code, designing FFI boundaries between safe and unsafe code, writing new modules in existing C/C++ codebases, reviewing mixed-language…
Investigate and remediate exactly one user-selected CodeInspectus finding with evidence-gated reproduction, a separately approved minimal patch, focused regression testing, and an exact-prior-scan rescan. Use when a user asks an agent to examine, reproduce, fix, or verify one CodeInspectus finding without batching…
Orchestrate an optional bounded multi-agent review of selected CodeInspectus findings while separating deterministic findings, agent interpretations, hypotheses, reproduction evidence, and exact-prior rescan proof. Use only when a user explicitly requests multi-agent security review.
Review CodeInspectus findings with optional threat-model or project-document context while treating repository text as untrusted, preserving raw scanner findings unchanged, and labelling agent interpretation separately. Use only when a user explicitly asks to add architectural, business, or knowledge-base context to…
AI code quality gate that detects hallucinated imports, phantom packages, stale APIs, and AI-specific code defects. Use when the user asks to scan code, review code quality, check for AI-generated bugs, audit imports, find phantom dependencies, or run a code quality gate. Supports TypeScript, JavaScript, Python, Java…
Write, format, and export professional academic research papers as publication-ready PDFs using reportlab. Use this skill whenever the user wants to write a research paper, preprint, white paper, literature review, position paper, or technical report — whether from scratch, from notes, or from an existing draft. Also…
Generate publication-grade ML explainer videos and carousels the way 3Blue1Brown actually builds them — in real manimGL (NOT Manim Community Edition), as a tiny domain DSL of self-arranging Mobjects choreographed into transform-driven beats where every motion carries meaning. Overlap is prevented at construction time…
Use this skill any time the user wants to FIND specific people online and put them in a spreadsheet — recruiting candidates, sales prospects, outreach lists, research participants, journalist sources, podcast guests, influencer lists, lead lists, beta testers, advisors, or hires. Triggers on "find me N people who…"…
Drift-spezifischer Workflow zum Erstellen und Verbessern von Agent-Prompts unter .github/prompts/. Verwenden bei neuen .prompt.md-Dateien, bei der Schärfung von Evaluierungs-Prompts, bei der Trennung zwischen internem Prompt und Field-Test-Prompt sowie bei der Ausrichtung auf Drift-Policy und Shared Partials.…
Erstellt und befüllt versioned feature-evidence Artefakte für feat:-Commits im Drift-Repo. Verwenden wenn ein benchmarkresults/-Artefakt für einen Feature-Commit fehlt oder unklar ist wie es benannt, strukturiert oder befüllt werden soll. Keywords: feature evidence, benchmarkresults, versioned evidence file, feat…
Diagnose and fix failing GitHub Actions workflows in the drift repository. Use when a CI run, security hygiene check, release workflow, or any other GitHub Actions job is red. Keywords: GitHub Actions, workflow failure, CI failure, failed run, failing check, red CI, workflow fix, gh run, action logs, pipeline error…
The door check for prototype and AI-built apps - decides whether an app gets to meet real users, and says exactly why not. Use this whenever someone asks if their app is ready to launch, deploy, or go live; wants a pre-launch, security, or "what am I missing" review; mentions moving from prototype to production; or…
Scan a repository for AI-generated technical, cognitive, and intent debt. Use when the user asks to audit a codebase for AI/vibe-coding risk, check for issues an AI coding assistant may have introduced (disabled RLS, hardcoded secrets, missing auth checks, SSTI, debug mode left on), assess technical debt after heavy…
Audit an AI-generated app for fake completeness — features that look finished in the UI but are not actually wired to anything. Traces every user-visible promise from the button to the database and back. Use when asked to run /vibeproof, to check if an app is really done, to find fake or dead UI, unwired buttons…