517 skills · sorted by relevance
Build an Opportunity Solution Tree, a structured map linking one measurable product outcome to customer needs, possible solutions, and experiments. Use research findings to prioritize problems and define hypotheses, metrics, and success thresholds for testing ideas.
Learn from top Kaggle solutions across text, images, time series, tabular data, and multimodal tasks that combine data types. Explore technical analyses, model settings, reusable code templates, and practical lessons to inform machine learning projects.
Learn from top Kaggle solutions across text, images, time series, tabular data, and multimodal tasks that combine data types. Explore technical analyses, model settings, reusable code templates, and practical lessons to inform machine learning projects.
Solve Diophantine equations (integer-only solutions) including linear, quadratic, and Pell equations. Covers the extended Euclidean algorithm, descent methods, and existence proofs. Use when finding all integer solutions to ax + by = c, solving Pell's equation, generating Pythagorean triples, proving no integer solutions exist via modular constraints, or finding the fundamental solution from which all others are generated.
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Search persistent claude-mem memories to recover past decisions, solutions, and work history. Review compact search results, surrounding context, and selected details, or let the tool handle these steps automatically for a clear query.
Store useful patterns and solutions in AgentDB, then find them through semantic search, which matches meaning rather than exact wording. Use saved knowledge before starting work and record successful approaches and new lessons afterward.
Develop independent solutions to a defined problem, compare them against shared requirements, and combine useful contributions into a coherent recommendation. An independent assessment and evidence checks support the selection, while unresolved tradeoffs and verification needs remain explicit.
Turn stakeholder requests into measurable goals, customer problems, possible solutions, and experiments. Through guided discussion, compare feasibility, expected impact, and customer fit to choose a proof of concept: a small test of a proposed solution.
Turn a recently solved research problem into searchable Markdown documentation. Capture symptoms, failed attempts, root causes, working code, and prevention checks, then organize the solution by category and link it to related records.
Expert knowledge for Azure Partner Solutions development including troubleshooting, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when integrating Confluent/MongoDB via Service Connector, managing Datadog/Dynatrace/Elastic/New Relic, or Palo Alto Cloud NGFW, and other Azure Partner Solutions related development tasks. Not for Azure Industry (use azure-industry), Azure Managed Applications (use azure-managed-applications), Azure Lighthouse (use azure-lighthouse), Azure Oracle (use azure-oracle).
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Alight Solutions integration. Manage data, records, and automate workflows. Use when the user wants to interact with Alight Solutions data.
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Audit and maintain the learnings in `docs/solutions/` against the current codebase — fix drifted paths and links, merge overlapping docs, replace guidance the code no longer supports, delete obsolete docs, reconcile the `CONCEPTS.md` glossary, then report and commit. Also bootstraps `CONCEPTS.md` on request and, when asked, culls docs whose reasoning the code already explains. Use for "refresh the learnings", "audit docs/solutions", "are our solution docs still accurate", "clean up / prune the learnings", "create a CONCEPTS.md", or after a refactor, rename, migration, or dependency upgrade that likely invalidated documented solutions. Not for capturing a new learning — use `learn-with-docs`.
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Research existing solutions before implementing a feature. Search project code, package registries, agent tools, and GitHub, then compare functionality, maintenance, licensing, and dependencies to decide whether to adopt, extend, combine, or build.
Create icon assets for iOS and macOS projects using SF Symbols or Iconify API. Match existing colors and sizes, then generate PNG files at three resolutions with the metadata needed for Xcode asset catalogs.
Find stored Ruflo memories by meaning, keywords, or an optional ranking method. Search across storage groups, retrieve past solutions and task context, and see which search method actually ran, including any fallback.
Use SymPy to simplify expressions, solve equations, and calculate derivatives, integrals, and matrices with exact symbolic results. Specify assumptions, verify solutions, and turn mathematical expressions into numerical functions, source code, or LaTeX output.
Solve optimization problems in Python with one or several competing goals. Define constraints, compare search algorithms, visualize trade-offs, and assess candidate solutions before choosing an option that fits your priorities.
Collects resolved questions and practical solutions in a project FAQ, checking for duplicates before adding or updating entries. It also searches saved keywords when new questions arrive, so relevant answers can be reused.
Record goals with measurable targets and deadlines, review progress against reported results, and update them as circumstances change. Keep a dated history in one file, with goal wording confirmed before it is saved.
Plan and explain Lakehouse solutions in Microsoft Fabric, a place to manage tables and files together. Understand data organization, links to data without copying, access controls, and table maintenance options for designing and improving a solution.
Turn a business use case into a Dataverse solution using Python. Get table and relationship designs, implementation code, usage instructions, and recommendations for error recovery, logging, monitoring, and performance based on the expected workload.
Explore product problems, generate alternative solutions, and challenge the assumptions behind an idea through conversation. It helps product managers compare directions, identify weak points, and choose questions or experiments to investigate before committing to development.
Route product questions to a specialist for prioritization, research, analytics, experiments, or implementation. Support recurring discovery by tracking interviews and assumption tests, checking how customer needs connect to proposed solutions, and returning results with a concise digest.
Summarize customer interview transcripts into a consistent Markdown document. Capture what customers want to accomplish, their current solutions, satisfaction and problems, notable findings, and follow-up actions with dates and owners when available.