1.3천건 · 관련도순
Run Scenic traffic scenarios on a CARLA server. First test whether a valid scene can be generated, then simulate with limits on runs and steps, record the outcome, and restore the world's asynchronous setting afterward.
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Use when hunting self-hosted GitHub Actions runner vulnerabilities where fork pull requests can execute on privileged non-ephemeral runners. Trigger on: "self-hosted runner", "runs-on self-hosted", "fork PR workflow", "non-ephemeral runner", "first-time contributor approval", "runner images", "azure-builds runner", "outside collaborator approval", "runs-on matrix", "persistent runner", "Gato GitHub Attack Toolkit", "runner agent", self-hosted CI/CD runner abuse, "git config token", "workflow log deletion", runner C2.
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Use on any core for first-run planning intake — Phase 0 runs the vendored BMAD-METHOD planning shelf, shared by every core, and Phase 1 (mining `04-prd.md` into intent records plus the Add-ons/sync-and-remote-entities decision) is full-stack-app's and pwa-app's shared procedure — identical mechanics, a different decision at step 5/8. Phase 0 also defines compressed intake, the path a user's explicit "just build it" choice takes on full-stack-app, pwa-app, authored, and copywriting cores: one batched round of questions in place of the shelf, writing a thinned archive at the same paths so Phase 1 (or, on copywriting, that core's own mining step), `ux-planner`, and the Re-entry pass all keep their documented source. Also use for the Re-entry pass, which mines new scope into additional intents without re-running the shelf, on any core with a module axis to add an intent to (full-stack-app, pwa-app, authored) — landing-page has none, so its own new-scope path runs through `hedgehog-landing-loop`'s Correction Protocol instead. Invoked by the `planner` agent, which decides the path; don't run standalone. landing-page runs this skill's Phase 0 on first run, then mines the same archive through `hedgehog-landing-loop`'s own planning-intake section, that core's counterpart to this skill's Phase 1. copywriting runs this skill's Phase 0 the same way (full or compressed), then mines the same archive through `hedgehog-copywriting-loop`'s own planning-intake section into a what/audience/register brief — no module axis, so its own new-scope path runs through that loop's Correction Protocol rather than the Re-entry pass below. An authored core runs this skill's Phase 0, then `hedgehog-core-design`, then this skill's Phase 1 mining against the designed layer sequence. A brownfield adoption (`hedgehog-adopt`) never runs this skill's shelf at all — the drivers BMAD elicits are already settled facts of a repo that already exists.
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Set up a repeatable build, launch, and debugging workflow for macOS apps using Xcode or SwiftPM, Swift’s package manager. A project script handles relaunching, connects to the Codex Run button, and supports logs and process checks.
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Product marketing and go-to-market strategy for B2B SaaS launches and positioning. Use this skill when planning a product launch, developing positioning and messaging, analyzing competitive landscape, building customer advocacy programs, designing a customer referral program (who may accept the reward, how the introduction is made), designing a win/loss interview program, working out why we lose deals, designing GTM strategy, creating category positioning, planning analyst briefings, or deciding which country to expand into and how far to localize. Also use it for an early-stage startup where the founder is still doing the selling — running founder-led sales, setting up a design-partner program, judging whether you have product-market fit, deciding what not to do yet, deciding when to hire the first AE or first marketer, and moving upmarket to larger buyers. Also use it when your company has just acquired another (or is about to), to plan the marketing integration: what you may and may not do between signing and close, the first letter to the acquired customers, whether to keep, endorse, fold in or retire the acquired brand, merging the two marketing databases without mailing people who opted out, when to start cross-selling, and announcing a product sunset. Also use it to design a demand-generation campaign and the channel plan it runs on: one campaign with one job, the offer for buyers who are and are not in market, what each channel is for, the kill and scale rules set before launch, the follow-up sales agrees to, the yearly calendar of always-on programs and tentpole campaigns, and which channels to keep, test or stop. Also use it for brand marketing and demand creation — how much to spend on brand versus performance, what to measure when a brand campaign produces no conversion event, and how to answer "we cannot attribute it". Also triggers on: founder-led sales, founder-led GTM, design partners, design partner agreement, first customers, first 10 customers, do we have product-market fit, PMF, Sean Ellis test, very disappointed survey, pre-seed, seed stage, when to hire our first AE, first sales hire, first marketing hire, moving upmarket, going upmarket, enterprise readiness, first enterprise deal, what do enterprise buyers need before they sign, positioning, product launch, beta program, early access program, design partners, private preview, public preview, general availability, GA launch, when can we call it GA, can sales sell a beta feature, selling the roadmap, launch tier, competitive intelligence, messaging, customer advocacy, win/loss analysis, win/loss interviews, why we lose deals, closed-lost analysis, loss reason, close-reason field, competitive displacement, displace an incumbent, rip and replace, competitive takeout, switch from a competitor, win deals from a competitor, incumbent contract, renewal window, auto-renewal notice period, switching costs, EU Data Act, cloud switching rights, why do we lose to no decision, GTM, category design, ideal customer profile, ICP, what is our real ICP, who actually buys from us, refresh our ICP from closed-won deals, ICP refresh before planning, analyst briefing, G2 review, international expansion, market entry, expand into Europe, which country should we launch in next, localization, translate our site, in-country go-to-market, regional GTM, is cold email legal in Germany, brand marketing, brand awareness, brand vs performance, brand versus demand gen, demand creation, demand capture, 95-5 rule, out of market buyers, category entry points, distinctive brand assets, mental availability, brand tracking, brand health, brand lift, share of search, how do we measure brand, justify brand spend, brand budget. Also triggers on public-sector marketing: sell to government, government marketing, public sector go-to-market, federal marketing, state and local government, SLED, FedRAMP, FedRAMP marketing claims, can we say FedRAMP ready, GovRAMP, StateRAMP, VPAT, accessibility confor
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Guide a first computer-use agent run from environment checks to a browser-only task and a viewer of the run history. Explain each stage so users can understand the output and review screenshots afterward.
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Run Openwork end-to-end tests, which verify complete user journeys, locally or on Daytona. Check the exact commit and runtime, investigate failures or skipped tests, and report results with commands, counts, and an explicit overall verdict.
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Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".
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Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".
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Runs Scenic probabilistic scenarios against a running CARLA server with the `scenic FILE --simulate --2d` CLI — the carlaChallenge1-10 traffic scenarios shipped by ScenarioRunner (`model srunner.scenic.models.model`) and by Scenic itself (`model scenic.simulators.carla.model`) — bounding the run, sampling scenes headlessly first to tell a map problem from a syntax problem, and restoring the world afterwards. Use when the user asks to "run a Scenic scenario", "run carlaChallenge", "test a .scenic file", "scenic --simulate", or reports a Scenic scenario that rejects every sample or cannot find blueprints.
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Set up first-pass for a main folder that holds many repos, or for one repo. In a main folder it writes one set of working rules at the root that every session loads, a workspace map, and a section in each repo with that repo's real commands, test limits and invariants, and it lists each repo's own hooks so first-pass can run them from the main folder. In one repo it writes the rules and the section into that repo. Use when asked to set up, install, add, update or re-run first-pass, to "add the shipping rules", or when the start-of-session check says something drifted. Re-run to update.
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Runs the test-first build loop (spec, plan, thin slices, failing test first, verify, commit) for a Godot 4 game in GDScript or C# first; in a TypeScript, Python or other repo when test-first, slices or a reproduce-first fix is asked for. Trigger to build or add a game feature, mechanic, stat, system or milestone, even when told to test later; to turn a spec or grill record into slices; to fix a game bug from a reproduction, one hypothesis at a time; on "write the test first", "what's the next slice", "is this slice done" or "is this milestone ready to exit"; or say slicesmith (spec, plan, slice, fix, exit). Run proof and gate rulings are godotsmith's; diff review a review tool's; repo maps researchscribe's; art pixelsmith's; audio soundsmith's; interviews grillwright's; fan-out dispatchwright's.
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Generate short videos with MiniMax H3 from text, starting images, or reference media. The skill guides camera and motion prompts, first-to-last-frame animation, and route selection across hosted services and local ComfyUI workflows.
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Scan a codebase to create project documentation and project-specific agent instructions. The first run examines the whole project; later runs focus on changed files, with human confirmation required before updating agent instructions after architectural changes.
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Set up automated testing before implementation begins. Detect the configured game engine, create test folders and runner configuration, and prepare a GitHub Actions workflow so tests can run automatically on each push.
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Helps individual developers get started on Google Cloud by checking local tools and authentication, selecting or creating a project, and linking billing. It verifies the setup and directs users to specialized guides for their first deployment.
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Save large text files when write_file or shell_agent encounters payload size limits. Create the parent directory first, write the content with Python through run_shell, and verify the resulting file.
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Run the oncall handoff for a rotation window — the whole handoff, not just a document: build the summary (what the incoming oncall needs first, what's still open, incidents with impact numbers, alert and page counts, hygiene suggestions, every number traceable to a source), post it for the outgoing oncall to correct, walk the incoming oncall through the open items in the thread, update the list as they respond, and note when they acknowledge. Runs mainly in the team's standing oncall / monitoring channel, normally as a scheduled routine firing at rotation change so the report is waiting when the shift turns over; can also be run by hand and works from an incident channel. Use when a handoff routine fires, or on "handoff", "hand over", "oncall summary", "weekly oncall report", "what happened this shift / this week". Re-running for the same window updates the report rather than duplicating it. Unattended runs carry a run-summary block and at least one chart.
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Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS"...
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Create a one-page service operations guide in HTML. It organizes service details, alerts and first responses, dashboard links, procedures with copyable commands, an on-call schedule, and an incident checklist so teams can find operational instructions together.
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Measure Storybook startup from launching the process to displaying the first story. Separate server readiness from browser rendering, summarize repeated runs, and compare versions or feature flags to investigate slower startup.
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Improve the experience after signup so new users reach a useful result sooner. Review setup steps, checklists, empty screens, and email triggers, then produce a prioritized audit or a redesigned flow with a measurement plan.
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Document a local codebase with file references, architecture diagrams, and verified project commands. For legacy modernization, assess what still runs and create a phased migration plan with validation methods suited to each component’s current condition.
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Connect a local CopilotKit agent to Slack through a managed Intelligence Channel. The skill guides dedicated Slack app creation, credential setup, runtime configuration, and checks that a human mention receives an actual reply.
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