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Topic: fastapi

399 skills in this topic.

remember Stores decisions and patterns in knowledge graph. Use when saving patterns, remembering outcomes, or recording decisions.
yonatangross/orchestkit 143
notebooklm NotebookLM integration patterns for external RAG, research synthesis, studio content generation (audio, cinematic video, slides, infographics, mind maps), and knowledge management. Use when creating notebooks, adding sources, generating audio/video, or querying NotebookLM via MCP.
yonatangross/orchestkit 143
help OrchestKit help directory with categorized skill listings. Use when discovering skills for a task, finding the right workflow, or browsing capabilities.
yonatangross/orchestkit 143
design-to-code Mockup-to-component pipeline using Google Stitch, 21st.dev, and Storybook MCP. Accepts screenshots, descriptions, or URLs as input and produces production-ready React components. Checks existing Storybook components before generating, orchestrates design extraction via Stitch MCP, component matching via 21st.dev registry, adaptation to project design tokens, and self-healing verification via run-story-tests. Use when converting visual designs to code, implementing UI from mockups, or building components from screenshots.
yonatangross/orchestkit 143
brainstorm Design exploration with parallel agents. Use when brainstorming ideas, exploring solutions, or comparing alternatives.
yonatangross/orchestkit 143
testing-perf Performance and load testing patterns — k6 load tests, Locust stress tests, pytest execution optimization (xdist parallel, plugins), test type classification, and performance benchmarking. Use when writing load tests, optimizing test execution speed, or setting up pytest infrastructure.
yonatangross/orchestkit 143
release-sync Sync release content to NotebookLM and HQ Knowledge Base after tagging a new version. Reads CHANGELOG, CLAUDE.md, and hook README, then updates notebook sources and ingests to knowledge base.
yonatangross/orchestkit 143
multimodal-llm Vision, audio, video generation, and multimodal LLM integration patterns. Use when processing images, transcribing audio, generating speech, generating AI video (Kling, Sora, Veo, Runway), or building multimodal AI pipelines.
yonatangross/orchestkit 143
golden-dataset Golden dataset lifecycle patterns for curation, versioning, quality validation, and CI integration. Use when building evaluation datasets, managing dataset versions, validating quality scores, or integrating golden tests into pipelines.
yonatangross/orchestkit 143
design-system-tokens Design token management with W3C Design Token Community Group specification, three-tier token hierarchy (global/alias/component), OKLCH color spaces, Style Dictionary transformation, and dark mode theming. Use when creating design token files, implementing theme systems, managing token versioning, or building design-to-code pipelines.
yonatangross/orchestkit 143
bare-eval Run isolated eval and grading calls using CC 2.1.81 --bare mode. Constructs claude -p --bare invocations for skill evaluation, trigger testing, and LLM grading without plugin/hook interference. Use when running eval pipelines, grading skill outputs, benchmarking prompt quality, or testing trigger accuracy in isolation.
yonatangross/orchestkit 143
testing-patterns Redirect — testing-patterns was split into 5 focused sub-skills. Use when looking for testing-patterns, writing tests, or test automation. Redirects to testing-unit, testing-e2e, testing-integration, testing-llm, or testing-perf.
yonatangross/orchestkit 143
release-management GitHub release workflow with semantic versioning, changelogs, and release automation using gh CLI. Use when creating releases, tagging versions, or publishing changelogs.
yonatangross/orchestkit 143
multi-surface-render Multi-surface rendering with json-render — same JSON spec produces React components, PDFs, emails, Remotion videos, OG images, and more. Covers renderer target selection, registry mapping, and platform-specific APIs (renderToBuffer, renderToStream, renderToFile). Use when generating output for multiple platforms, creating PDF reports, email templates, demo videos, or social media images from a single component spec.
yonatangross/orchestkit 143
github-operations GitHub CLI operations for issues, PRs, milestones, and Projects v2. Covers gh commands, REST API patterns, and automation scripts. Use when managing GitHub issues, PRs, milestones, or Projects with gh.
yonatangross/orchestkit 143
design-context-extract Extract design DNA from existing app screenshots or live URLs using Google Stitch. Produces color palettes, typography specs, spacing tokens, and component patterns as design-tokens.json or Tailwind config. Use when auditing an existing design, creating a design system from a live app, or ensuring new pages match an established visual identity.
yonatangross/orchestkit 143
audit-skills Audits all OrchestKit skills for quality, completeness, and compliance with authoring standards. Use when checking skill health, before releases, or after bulk skill edits to surface SKILL.md files that are too long, have missing frontmatter, lack rules/references, or are unregistered in manifests.
yonatangross/orchestkit 143
testing-llm LLM and AI testing patterns — mock responses, evaluation with DeepEval/RAGAS, structured output validation, and agentic test patterns (generator, healer, planner). Use when testing AI features, validating LLM outputs, or building evaluation pipelines.
yonatangross/orchestkit 143
release-checklist Validates release readiness with gated checklist — build, test, count validation, changelog, version bump. Use when preparing a release.
yonatangross/orchestkit 143
monitoring-observability Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse v4 LLM tracing (as_type, score_current_span, should_export_span, LangfuseMedia), and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring.
yonatangross/orchestkit 143
fix-issue Fixes GitHub issues with parallel analysis. Use when debugging errors, resolving regressions, fixing bugs, or triaging issues.
yonatangross/orchestkit 143
demo-producer Creates polished demo videos for skills, tutorials, and CLI demonstrations. Use when producing video showcases, marketing content, or terminal recordings.
yonatangross/orchestkit 143
honcho-integration Integrate Honcho memory and social cognition into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, implementing the dialectic chat endpoint for AI agents, or wiring Honcho into bot frameworks (nanobot, openclaw, picoclaw, etc).
plastic-labs/honcho 2,088
migrate-honcho Migrates Honcho Python SDK code from v1.6.0 to v2.1.1. Use when upgrading honcho package, fixing breaking changes after upgrade, or when errors mention AsyncHoncho, observations, Representation class, .core property, or get_config methods.
plastic-labs/honcho 2,088