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A GitHub Copilot skill from the awesome-copilot collection that helps AI agents systematically review Oracle to PostgreSQL migration code for correctness and compatibility issues.

One-shot publisher that converts PPTX, PDF, HTML, or Google Slides into a live GitHub Pages URL — handling repo creation, file conversion, Pages enablement, and large-file external-asset mode automatically. Uses the gh CLI plus python3 (and optional poppler-utils) under the hood.

A GitHub Copilot skill from the awesome-copilot collection that helps AI agents write, analyze, and run CodeQL queries for automated security vulnerability detection.

Guidance for creating, refactoring, and reviewing Microsoft Agent Framework applications (the unified successor to Semantic Kernel and AutoGen), with separate workflows for .NET and Python. Because the framework is still in public preview, the skill always grounds advice in the latest official documentation rather than stale knowledge.

Write and review behaviour-first unit tests for Vue 3 + TypeScript + Vitest + Pinia codebases, with guidance on createTestingPinia, Vue Test Utils patterns, and avoiding implementation-coupled assertions. Tests stay small, deterministic, and assert observable inputs/outputs (rendered text, emitted events, store state changes).

Generates and edits draw.io (`.drawio`, `.drawio.svg`, `.drawio.png`) diagrams with valid mxGraph XML — flowcharts, system architecture, sequence/UML class/ER diagrams, network topology, and BPMN — that open immediately in the `hediet.vscode-drawio` VS Code extension or draw.io web/desktop app. Includes a templated workflow (request → layout → XML → save → optional Python validator) plus a semantic color palette and ready-to-use style strings per diagram type.

Installs npm packages in Docker sandbox environments whose workspace is mounted via virtiofs — where native binaries like esbuild, lightningcss, and rollup crash with SIGILL/SIGSEGV. Works around the issue by installing on the container local ext4 filesystem and symlinking node_modules back into the workspace.

Modern Spring Boot 4 testing guide built around the test pyramid, picking the narrowest slice that gives confidence, and using AssertJ plus MockMvcTester / RestTestClient over legacy alternatives. Covers `@WebMvcTest`, `@DataJpaTest`, `@RestClientTest`, `@JsonTest`, and `@SpringBootTest` with reference material for each slice.

Practical guidance for designing product-led growth motions — deciding PLG vs sales-led, optimizing activation, driving freemium-to-paid conversion, and spotting when product complexity requires a human touch. Includes a real case where running PLG and sales-led in parallel showed sales-led winning 10x on revenue despite 10x lower volume.

Launch playbook for going from idea to first 10–50 customers, covering press-vs-growth trade-offs, launch-week planning, diagnosing why adoption stalls, and a three-layer diagnosis/two-week experiment cycle. Includes the real launch that got 50K impressions but only 12 signups and what actually worked better.

GTM playbook for AI products — positioning ("copilot" vs "agent" vs "teammate"), handling the real enterprise objection ("who is responsible when the agent breaks production?"), pricing variable-cost AI, and selling autonomous tools into enterprise ops. Built from field experience selling AI agents where security passed but operations rejected the product.

Pricing strategy playbook for technical products, covering usage-based vs seat-based choices, freemium thresholds, enterprise pricing conversations, and timing price increases. Includes the case of an enterprise tier going from $15K to $45K/year with zero churn and 3x revenue per account.

A GitHub Copilot skill from the awesome-copilot collection that helps AI agents manage and execute go-to-market operating cadence workflows for product launches and sales cycles.

Resolves .NET/C# timezone questions by routing to the right library — `TimeZoneInfo` for Windows-only, `TimeZoneConverter` for cross-platform, `NodaTime` for strict DST/scheduling, `DateTimeOffset` for APIs — with both Windows and IANA IDs and copy-paste-ready snippets. Looks up time zones for arbitrary addresses/cities/countries via `references/timezone-index.md` and warns on common pitfalls (`DateTime.Now` in DBs, ambiguous DST timestamps, Azure Linux vs Windows IDs).

Pipeline that designs Azure infrastructure from natural language or analyses existing resources, then generates interactive HTML diagrams (605+ official Azure icons via bundled Python — no `pip install`) and ships Bicep IaC. Routes between Path A (Phase 1 advisor → Phase 2 Bicep generator → Phase 3 reviewer → Phase 4 validate/what-if/deploy) and Path B (Phase 0 scanner → modification dialog → Phase 1+) and auto-detects user language to localise all output.

Explores any codebase first (domain, architecture, specs, failure history, optional AI chat-history mining) and then generates six grounded artefacts: `quality/QUALITY.md` constitution, language-appropriate spec-traced functional tests, `RUN_CODE_REVIEW.md` with anti-hallucination guardrails, `RUN_INTEGRATION_TESTS.md`, a Council-of-Three multi-model `RUN_SPEC_AUDIT.md`, and an `AGENTS.md` bootstrap file. Designed to go beyond test-stub generators and prevent generic "coverage theatre" by tying every output to specific functions, schemas, or defensive patterns in the actual code.

Helps network operators (ISPs, carriers, cloud/hosting providers, IXPs) create, validate, and improve self-published RFC 8805 IP geolocation feeds in CSV — well-formedness checks, RFC 8805 compliance, and opinionated best-practice tuning beyond the standard. Runs a strict 6-phase pipeline (standard review → input → checks/suggestions → Fastah MCP tuning lookup → HTML report → final review), keeps `assets/`/`references/`/`scripts/` read-only and writes all generated files under `./run/`. Public IPs only — not for private/internal address management.