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Found 3,129 Skills
Creates and edits Excel spreadsheets with formulas, formatting, and financial modeling standards. Use when working with .xlsx files, financial models, data analysis, or formula-heavy spreadsheets. Covers formula recalculation, color coding standards, and common pitfalls.
Use when the user wants to build a Python Kafka producer or consumer, add Schema Registry to existing Python code, migrate from raw JSON to schema-backed serialization, or scaffold a confluent-kafka-python project for Confluent Cloud, local Docker, or WarpStream. Also use when user wants to optimize Python Kafka client configuration for WarpStream.
Enforces classNames package usage patterns and Tailwind CSS class ordering conventions in React components. Use this skill whenever writing or reviewing component className props, applying Tailwind classes, using the classnames package, organizing breakpoint-specific styles, writing conditional class expressions, or when the user asks about CSS class ordering, mobile-first responsive patterns, or how to handle className props in components.
Create a complete SPEC from scratch through an exhaustive requirements interview before any planning or implementation. Use this skill whenever the user asks to create, define, clarify, scope, or write a spec/SPEC/PRD/requirements document from an idea, especially when they want to avoid assumptions, start at "step zero," or prepare input for later planning workflows. This skill must question goals, requirements, constraints, edge cases, business rules, and acceptance criteria before drafting the final spec.
Builds trade area and catchment analysis workflows in CARTO. Triggers when the user mentions trade area, catchment area, isochrone, site selection, where to open, best location, billboard, OOH, audience targeting, drive time, walk time, coverage area, commercial hotspot, site scoring, location ranking, or wants to generate isochrones, score candidate locations, or identify the best sites for retail, advertising, or services.
Vendor-neutral skill to track security exception expirations and generate remediation reminders.
Core Oodle CLI usage — auth, output formats, time flags, file input, and common patterns for all oodle commands.
Manage Oodle notifiers, notification policies, and muting rules — routing alerts to the right channels and silencing during maintenance.
Eight-axis judgment code review for the current diff — Correctness, Simplification, Tests, Documentation, Style, Intent, Design/API, Performance (+ Coherence on metadata changes). Five-phase pipeline scope → deterministic tool battery (npx/uvx-preferred, zero-install for the JS + Python majority) → 8 parallel LLM axis reviewers → Haiku validators on sub-80 findings (verbatim rubric, ≥80 threshold) → synthesis with no-silent-drop + Conventional Comments JSONL. Every report closes with "What I did NOT check" (security → /security-review, runtime perf, flaky detection). Opt-in flags `--verify-build`, `--mutation-test`, `--reconcile`, `--apply-safe`. Public-skill posture — zero auto-install, graceful skip on missing native tools.
Decision frameworks for DatoCMS content modeling — schema shape, field choice, content reuse, taxonomies, content vs presentation, admin UI organization. Use for modeling *decisions*, not implementation: model vs block; single_block vs Modular Content vs Structured Text; references vs embedded blocks; taxonomy shape (flat/tree/faceted); refactoring page-shaped schemas to reusable content; fitting 300 KB / 500-block / 5-level record limits; model behaviour (singleton, draft mode, all_locales_required, sortable/tree/ordering_field, presentation_title_field, collection_appearance, inverse_relationships_enabled); field config (validator + appearance — enum + string_select, slug auto-fill, required_alt_title, structured_text allowlists, framed vs frameless single_block). Also schema review (reuse, editor ergonomics, omnichannel). *Creating* schema → `datocms-cli` or `datocms-cma`. Query/render → `datocms-cda` + `datocms-frontend-integrations`. Validators + cascade: `datocms-cma/references/schema.md`.
Investigate a Datadog product usage or cost spike by correlating Usage Metering data (when/what spiked) with Audit Trail config changes (who changed what in the preceding window).
Audit Trail investigations - who changed what, key compromise, cost spike root cause, compliance evidence (SOC 2/PCI), and AI activity auditing.