Skill UI

This guide provides best practices for authors submitting to top-tier technical conferences. It clarifies the critical distinction between core, review-essential arguments (which must stand alone in the main paper) and supporting evidence (such as formal proofs, extra data analyses, or methodological details) suitable for an optional supplementary document. It also covers anonymity best practices and distinguishing between different submission types.

A detailed guide for authors submitting theoretical computer science papers, outlining the required evidence objects (proofs, certificates, code) and best practices for preparing the public, full version of the work. It emphasizes structuring arguments to meet the standards of top-tier academic conferences like STOC.

Guidelines for ensuring academic proofs are completely verifiable by third parties, especially when theorems are distributed across multiple documents (e.g., extended abstract and full version). It emphasizes single-source builds, preventing statement drift, and detailing computational determinism requirements for maximum rigor in theoretical computer science research.

A comprehensive guide for allocating content across academic conference submissions, ensuring critical evidence is visible within strict page limits. It defines rules for triaging material into decisive (body), supporting (appendix/repo), and archival (repository) categories, along with advanced compression tactics for tables and proofs.

This guide outlines best practices for structuring supplementary materials for OOPSLA submissions. It emphasizes the 'layering decision,' ensuring the core body can stand alone while appendices provide necessary proofs and technical details. It covers maintaining double-anonymity across all included content and performing crucial cross-checks for consistency across multiple review rounds.

This framework applies the Lindy Effect principle to assess the expected remaining life of non-perishable technologies, ideas, or practices. It treats the current survival age as a strong prior for future longevity, guiding users to favor proven, long-surviving options. It is crucial when making critical, high-stakes choices (like selecting frameworks or protocols) where relevance must last years, requiring checks for domain drift and a clear burden of proof before adopting novelty.

Generates a declared number of independent candidates for a high-stakes task, scores them against a frozen rubric, and verifies the selected result with executable checks and a proof log. Use when multiple plausible solutions exist and a wrong choice is costly.

A deep-dive methodology for authorized penetration testing targeting dependency confusion and namespace resolution vulnerabilities across major package ecosystems (npm, PyPI, NuGet, Maven, etc.). This skill details advanced reconnaissance techniques, from analyzing lock files and source maps to exploiting error messages, alongside safe Proof-of-Concept (PoC) creation using DNS canaries for discovery during penetration engagements.

This skill guides the advanced process of reverse engineering vulnerabilities from vendor-released security patches (N-day). By performing binary diffing between patched and unpatched binaries, users can pinpoint specific code changes (e.g., new boundary checks, locks) to infer the original vulnerability class (e.g., OOB, Race Condition) and develop a working Proof of Concept (PoC) for weaponization.

A disciplined methodology for fixing bugs and small behavioral changes with minimal impact. It involves tracing symptoms to the narrowest responsible mechanism, implementing changes only at that layer, and adding highly focused regression proofs to ensure surrounding functionality remains intact. Ideal for critical systems requiring maximum stability.

A specialized workflow for validating existing work against strict acceptance criteria without expanding scope or modifying product code unnecessarily. Use this function for focused gate runs, completion checks, and last-mile proofing. It ensures that only the necessary proof set is executed, precisely reporting pass/fail status and unresolved risks, and stopping immediately upon successful validation.

This skill extracts a checklist from planned work, builds the implementation, and verifies every check with an independent verifier. It is used when the user requests to extract a checklist, build a ticket, or implement a spec. It ensures rigorous testing and proof-based assertions, preventing self-reporting of completion. It involves extracting checks, building the code, and proving each one independently to guarantee quality.