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Found 1,839 Skills
Enqueues jobs, configures retry policies, sets concurrency limits, and orders messages via named standard or FIFO queues. Use when building background job workers, task queues, message queues, async pipelines, or any pattern needing guaranteed delivery with exponential backoff and dead-letter handling.
DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; add tracing or @observe; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, tracing, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval.
Design and operate data quality programs for financial data — golden source architecture, validation rules, data lineage, exception management, profiling, and governance. Use when building validation rules for pricing or client data pipelines, designing a data quality monitoring framework, establishing golden source designations across systems, implementing data lineage for BCBS 239 or MiFID II, investigating reconciliation breaks or billing errors traced to bad data, preparing for regulatory exams on data accuracy, building data quality scorecards, or defining data stewardship roles. Trigger on: data quality, golden source, data lineage, data validation, data profiling, exception management, data governance, BCBS 239, data completeness, data accuracy, validation rules, data anomaly, data stewardship, data quality scorecard.
Guides CI/CD for agent skills repositories and skill packages—pipeline design (build, test, validate, package), GitHub Actions for PR checks and release promotion, environment gates, secrets hygiene (no secrets in repo), skill-creator integration (quick_validate.py, package_skill.py), .skill artifact strategy, rollback, and operational runbooks for skill releases. Use when the user mentions CI/CD, CI/CD engineer, pipeline design, GitHub Actions, skill validation CI, package skills, release pipeline, deploy skills, PR checks, continuous integration, or skill release workflow—not application-only CI without skill packaging (devops), pre-flight plan go/no-go (build-validator), IDP or golden paths (platform-engineer), org-wide SLO and error-budget programs without pipeline ownership (site-reliability-engineer), or portfolio catalog governance without pipeline YAML (ai-skill-manager).
Build Docker images for Python services following team conventions. Use this skill when writing Dockerfiles, authoring CI image build pipelines, or adding a new service — covers mitodl image naming, git short-ref tags, relocatable uv venvs, and shared library handling.
Full UGC ad video pipeline — generates a character image on Higgsfield, then creates a Seedance 2.0 video from it. Orchestrates the complete flow from image prompt to finished UGC video. Use when the user wants to create a UGC ad video end-to-end, or wants to take a generated image from Higgsfield's image tab into video creation. Triggers on "create a UGC video", "make a UGC ad", "UGC pipeline", "turn this into a UGC video", or any request combining image generation with video creation for ads/UGC content. Requires Playwright MCP tools.
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.
Automated AI content pipeline from research to video generation using Claude/OpenAI and Remotion
Designs and optimizes Clay-powered GTM workflows for prospecting, signal detection, outbound email sequences, enrichment pipelines, and account-based marketing. Use when the user mentions 'Clay,' 'GTM engineering,' 'prospecting,' 'signal detection,' 'enrichment,' 'Claygent,' 'outbound automation,' or wants to build Clay tables or integrate with sequencing tools like Lemlist, Smartlead, or Instantly.
Use when triggering a post-merge deployment after a PR is merged (stage 1 of the post-merge pipeline).
Generate game assets using AI image generation APIs (DALL-E, Replicate, fal.ai) and prepare them for Godot. Covers the full art pipeline from concept art and style guides to final sprites, sprite sheets, and import configuration. This skill should be used when creating game art, generating sprites, making tilesets, creating UI elements, or preparing assets for Godot import. Keywords: game assets, AI art, DALL-E, Replicate, fal.ai, sprite sheet, tileset, Godot, pixel art, character sprite, game art, texture, animation frames.
[Extended thinking: This workflow implements a sophisticated debugging and resolution pipeline that leverages AI-assisted debugging tools and observability platforms to systematically diagnose and res