Skill UI

This guide provides a systematic approach to deep debugging complex HubSpot API issues. It includes layer-by-layer network testing (DNS, TCP, TLS), correlation ID tracking, and timing analysis to isolate intermittent or hard-to-reproduce errors. Use this when standard troubleshooting fails or when compiling detailed evidence for technical support.

Provides a comprehensive setup guide for running ClickHouse locally using Docker Compose. This includes defining the database schema, seeding mock data, and setting up robust integration tests (using vitest). Ideal for developers building OLAP systems or performing local data analysis to ensure schema and query reliability.

This skill acts as the interactive command center for the Freshie ecosystem's CMDB. It tracks plugins, skills, and packs, providing comprehensive health checks, compliance validation, and historical trend analysis across 50 tables. Use it for running discovery scans, auditing compliance grades, querying deep inventory data, or generating detailed status reports.

This structured skill guides users through root-cause-first debugging when an implementer is blocked, verification fails, or repeated attempts at fixing do not converge. It mandates a systematic approach combining local evidence inspection, runtime analysis, and external documentation research to accurately classify the failure's true source (e.g., missing dependency, spec conflict). It prevents speculative patching and generates a clear, actionable fix plan.

A comprehensive guide detailing advanced offensive fuzzing methodologies. It covers the full lifecycle from target identification (parsers, network protocols, kernels) to tool selection (AFL++, libFuzzer, Honggfuzz, syzkaller), building harnesses, curating seed corpora, executing fuzz campaigns, and finally, performing crash triage and vulnerability analysis. Essential for security researchers and embedded systems developers.

This skill provides a comprehensive, paragraph-level structural blueprint for writing top-tier systems conference papers (e.g., OSDI, SOSP, ASPLOS). It meticulously outlines page allocation, section-specific templates (like the 5-sentence abstract or Problem-Gap-Insight structure), and rigorous writing patterns (Gap Analysis, Observation-Driven) required for industry-leading academic submissions.

The Desktop Commander MCP grants agents deep reach across the user's entire operating environment, extending far beyond the typical IDE sandbox. Key capabilities include maintaining persistent shell sessions, managing long-running background processes, accessing arbitrary filesystems, and natively handling structured data formats (Excel, PDF, DOCX). It also enables remote operations via SSH and large-scale content search, making it ideal for complex, multi-turn development, DevOps, and data analysis workflows.

A comprehensive workflow and deep technical guide for analyzing malicious Linux ELF binaries. Covers static analysis (reading ELF headers, checking entropy, identifying strings), dynamic tracing (monitoring system calls and library usage with strace/ltrace), and reverse engineering (using GDB) of threats like ransomware, botnets, and rootkits targeting Linux servers and containers (x86_64, ARM).

This comprehensive guide covers the process of creating, analyzing, and securing Software Bills of Materials (SBOMs). It utilizes Syft to generate standards-compliant SBOMs (CycloneDX or SPDX) from container images and filesystems. The workflow details correlating these SBOMs with known CVEs using Grype for vulnerability analysis, and subsequently signing the artifacts with Cosign. This process is crucial for establishing supply chain trust, ensuring dependency visibility, and integrating vulnerability gating into CI/CD pipelines.

A systematic, non-mutating investigation designed for complex software failures, including bugs, regressions, crashes, and flaky behavior. This skill launches four specialized, read-only sub-agents in parallel to perform deep root-cause analysis, trace code paths, pinpoint the smallest failing seam, and predict the quickest path to confirming or fixing the issue. It is designed purely for diagnosis and hypothesis generation.

A comprehensive, four-phase methodology for debugging complex software issues. It guides users through root cause investigation, pattern analysis, hypothesis testing, and controlled implementation. The core principle emphasizes finding the underlying cause rather than applying quick, symptomatic fixes, ensuring robust and reliable code improvements across various failure scenarios.

This sophisticated skill is designed to locate the root cause of a confirmed software failure. It performs a systematic, semi-formal tracing process: first tracing backward from the observed failure point (using provided stack traces, assertions, or error messages) to identify the original premise, and then tracing forward to confirm the symptom. It outputs a highly structured report detailing the divergence, premises, and remedy.