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Found 6,096 Skills
Query and analyze a Dynatrace tenant's ACTUAL billing and usage data with DQL against dt.system.events — DPS consumption breakdown, cost-normalized spend ranking, included volume deduction, chargeback/showback, cost drivers, spending trends, cost investigation, metrics ingest optimization, query cost attribution, workflow total cost, and entity-level cost drill-down (RUM, hosts, synthetic, K8s). Also directs licensing/entitlement questions to the right resource (not available via DQL). USE ONLY to query/analyze the tenant's actual consumption. Do NOT use for conceptual 'explain' questions about how DPS billing/pricing works or what units/weights/the rate card mean — those belong to Dynatrace documentation. Also do NOT use for making a DQL query itself faster or cheaper to run (query optimization, reducing scanned data/consumption per run, filter-early best practices) — that belongs to dt-dql-essentials. This skill only MEASURES recorded consumption; it does not tune queries.
Query OpenRouter's Benchmarks API for model benchmark rankings and scores. Use when the user asks for benchmark-backed model selection, model rankings by coding/intelligence/agentic ability, Artificial Analysis or Design Arena ELO/win-rate results, benchmark citations, or wants to call GET /api/v1/benchmarks. Also use alongside openrouter-models when the user asks what model should power an app, product, workflow, or use case and benchmark evidence could inform or rule out part of the recommendation, including creative writing, editing, coding, design, agentic, or intelligence-heavy apps. Do not use for OpenRouter usage analytics, billing/spend analysis, generation metadata, provider uptime/latency, generic model pricing/capability lookup without any selection or benchmark-relevance decision, or creating an evaluation suite for a local app.
Graph engineering for parallel task execution: convert a task, PRD, SPEC, or issue set into a dependency graph (DAG), layer it into supersteps, then implement each independent node concurrently with subagents — each node runs /goal → /review-it → /ship-it in an isolated git worktree, with a fan-in barrier between waves. Triggers on: graph, graph engineering, build a graph, task graph, dependency graph, DAG, parallel implement, 并发实现, 并行实现, 任务图, 把任务变成图, fan-out fan-in, superstep, dynamic workflow.
Take a PRD and build a dark factory around it - a repository that takes work in as an issue and ships validated code out with nobody at the keyboard - one component at a time, into the user's actual repo. Covers the five components in construction order - the guidance layer, the validation harness, the workflow-driven repo, deployment, and the trigger that makes it autonomous - and is agnostic about which coding agent runs underneath (Claude Code, Codex, Archon, the Agent SDK, Cline, Goose, Amp, Pi). It encodes the AI coding process the user already runs rather than replacing it. Requires a PRD as input and deliberately does not write one. Use when the user wants to build a dark factory, an autonomous or self-driving repository, a software factory, an agent that ships its own code, an unattended or overnight coding loop, or asks how to get to level 4 or level 5 of AI coding autonomy; and when they mention dark factory, lights-out coding, autonomous PRs, or a repo that maintains itself.
Run Git and GitHub CLI commands through the host context when sandboxing blocks Keychain authentication, network access, or .git writes. Use for gh auth, repository or PR operations, and git index.lock or permission failures. Handles execution context only, not GitHub workflow design.
Lewis's backtest workflow. Drop a strategy idea in, get a structured backtest plan and results template back.
Create and export technical, product, architecture, and process illustrations in 27 formats—including architecture, IT current-state, flowchart, sequence, state machine, ER, timeline, swimlane, quadrant, radar, loop, nested, tree, org chart, layers, venn, pyramid, bar, line, Gantt, scatter, high-level, process, medallion, data flow, DP integration, and DP security matrix—as standalone HTML with inline SVG plus optional SVG/PNG/PDF exports. Use for diagram generation, architecture diagrams, process flows, workflow maps, visual variants, project-level light/dark theme and font initialization, brand onboarding, and diagram export. Incorporates the complete former architecture-diagram and process-flow-diagram skills as first-class technical-color families, alongside editorial light/dark/full/hand/terminal/consultant treatments and built-in Copy/PNG/PDF controls.
Produce media assets using AnyCap: generate images, videos, music, speech, dialogue, and complete audio scenes from text or reference inputs, refine images through interactive visual annotation, and deliver finished assets. Covers the full production workflow from concept to delivery across all media types (image, video, music, audio). Use when creating images, videos, music, voice content, dialogue, complete audio scenes, or any visual/audio content -- including iterative refinement with human feedback. Also use for image-to-image transformation, video generation from images, audio generation from references, and annotation-driven precise edits. Trigger on: media production, asset generation, generate image/video/music/audio, create visual content, produce assets, iterative image editing, annotate and refine, creative workflow, content creation, or any task requiring AI-generated media output.
Interact with GitHub, GitLab, Gitea, Forgejo, Codeberg, and Bitbucket repositories through one CLI. Use instead of `gh` or `glab` when the git remote is not github.com, when working against a self-hosted forge, or when the same workflow needs to run unchanged across forges. Covers pull/merge requests, issues, releases, CI pipelines, labels, and repo management.
Read as a specified first-time reader persona and report the felt experience. Use for skill-only workflows when a draft needs persona-bound reader-response signal instead of analytical critique.
Coordinate end-to-end HPC execution workflows across scheduler submission, job monitoring, log tracking, self-healing, and post-processing handoff. Use when a task spans Slurm, PBS, LSF, MPI sizing, queue operations, cluster-safe execution, or multi-stage HPC workflow orchestration.
Generate, review, debug, and recover OpenFOAM case files for CFD workflows. Use when working with OpenFOAM dictionaries, case structure, turbulence fields, boundary conditions, decomposition, numerics, or OpenFOAM runtime errors. Also covers RANS/LES turbulence setup, wall functions, y+ targeting, conjugate heat transfer, compressible flows, VOF multiphase, mesh quality, and scheme tuning.