「gates」の検索結果

Gates CI on perf regressions. Automated threshold alerts, baseline tracking, trend reports.

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Build and maintain CI/CD pipelines, containerization, Kubernetes manifests, and quality gates. Use when tasks involve Docker, Kubernetes, GitHub Actions/Azure DevOps pipelines, deployment, reliability, or static analysis workflows.

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Build and maintain CI/CD pipelines, containerization, Kubernetes manifests, and quality gates for this repository. Use when the user asks for Docker, Kubernetes, GitHub Actions/Azure DevOps pipelines, deployment, reliability, or static analysis workflows.

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Build and harden high-performance APIs with strong security controls, endpoint budgets, rate limiting, and resilience patterns. Use when tasks involve API latency/throughput tuning, abuse resistance, authz hardening, or API release gates.

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Use when building, testing or previewing site-os — the BUILD_TARGET=stable dist directory, the four verification gates (build, test, env:check, brand:check), the preview servers on :3000 and :3100, and the failure modes that look like bugs but are not.

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Orchestrate the migrate-prep cascade — extract --prep → direct --prep → prototype --prep → assets prep — with confirmation gates between phases. Builds the data structure migrate consumes.

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Guided multi-page redesign of an existing website through a four-phase pipeline — extract (crawl and capture the current site), direct (set a visual direction), prototype (generate redesigned HTML), and migrate (emit a deployable static site). Tracks progress incrementally per page in stardust/state.json so redesigns are resumable. Delegates the per-page design craft (typography, spacing, color, layout, motion) to the impeccable skill. Use when the user wants to redesign, revamp, modernize, or restyle an existing site they can point to by URL, run the extract/direct/prototype/migrate flow, or resume a multi-page redesign. Not for designing a brand-new site from scratch or one-off single-component edits.

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Silent failure hunting routing. Use when a change might pass while skipping work, swallowing errors, losing evidence, weakening gates, or reporting false success; do not use for broad code review.

日本語の概要は準備中です。原文の説明を表示しています。

Code-review quality gate and test-enhancement rubric. Use when ROSE needs sharper review output contracts, severity and risk prioritization, evidence anchors, negative review cases, fixture or golden-output drift guidance, or a Chinese review report profile; do not use as a duplicate code-review agent or final PASS authority.

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Configure or modify concrete CI/CD pipelines, jobs, quality gates, test runners, or deployment automation; do not trigger merely because an existing CI gate failed or ordinary source code needs repair.

日本語の概要は準備中です。原文の説明を表示しています。

Creates repeatable security review checklist for PRs with required checks, common pitfalls, and automated gating. Use for "security review", "PR checklist", "code review", or "security gates".

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Bug bounty report writing for H1/Bugcrowd/Intigriti/Immunefi — report templates, human tone guidelines, impact-first writing, CVSS 3.1 scoring, title formula, impact statement formula, severity decision guide, downgrade counters, pre-submit checklist. Validation gates and the submittability/always-rejected decision are owned by triage-validation; this skill owns the written report itself (templates, tone, formulas). Use after validating a finding and before submitting. Never use 'could potentially' — prove it or don't report.

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Finding validation before writing any report — 7-Question Gate (all 7 questions), 4 pre-submission gates, always-rejected list, conditionally valid with chain table, CVSS 3.1 quick reference, severity decision guide, report title formula, 60-second pre-submit checklist. Use BEFORE writing any report. One wrong answer = kill the finding and move on. Saves N/A ratio.

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AI-powered autonomous data extraction that navigates complex sites and returns structured JSON. Use this skill when the user wants structured data from websites, needs to extract pricing tiers, product listings, directory entries, or any data as JSON with a schema. Triggers on "extract structured data", "get all the products", "pull pricing info", "extract as JSON", or when the user provides a JSON schema for website data. More powerful than simple scraping for multi-page structured extraction.

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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Produce a set of product images to choose between — several styles, backgrounds or treatments of one product, for a listing, a store page or an ad — and quote the whole set's cost before any of it is spent. From a real product photo it edits that photo once per style, so the item stays identical across the set; for a fictional or prototype product with no photo it generates from text instead, and says what that costs in accuracy. Delegates to ofox-image-core. Use when a user asks for several product images at once, e.g. "give me 4 main images in different styles for this product", "a few background options for this photo", "some listing images for my shop", or "show this product on white, on wood, and in a lifestyle scene". Do not use for a single change to a single image (see image-edit), for video from a product photo (see seedance-product-video), or for one plain text-to-image render (that is ofox-image-core's `generate`).

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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Change one thing in an image you already have and leave the rest of the picture alone — swap the background, recolour a part, remove or add an object, clean up a photo — from a local jpeg/png/webp file. Delegates to ofox-image-core's `edit` subcommand (POST /v1/images/edits, one synchronous request), prices the job with --dry-run before spending, and reports the real token cost including the uploaded picture, which is billed. Use when a user hands over an image and asks for a change to it, e.g. "change the background of this photo to a beach and keep the person unchanged", "make this button green", "remove the car in the background", or "put this product on a plain white background". Do not use to draw a new image from a text description with no input picture (that is ofox-image-core's `generate`), to produce a set of several images to choose between (see product-image), or to turn a photo into video (see seedance-product-video or seedance-ad-creative). Editing the content of an existing video — "change the background of my clip, keep the product" — has no route here and none in the video API either (measured; the mode field an edit would use is accepted and silently ignored, so nothing errors); this skill edits a single still, and routing such a request to a video skill generates brand-new footage instead of changing theirs.

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Generates and delivers all outreach for OUTREACH_READY leads. Automated delivery via Chrome DevTools MCP -- email, LinkedIn, Instagram. Gig leads auto-applied on platform. No approval gates.

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Refute-before-prove research discipline: automated counterexample sweeps before any formalization, meter-integrity audits for information-bound experiments, mutation-tested model checkers, pre-registered commit-or-cut gates for speculative directions, wrong-turn reporting, and numeric-claim provenance. Use when validating any new theorem, bound, equilibrium, or security claim; when building or trusting a checker, simulator, or experiment; or when deciding whether a speculative research direction lives or dies. NOT for exploratory brainstorming, product prioritization, writing style, or literature review.

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Audit whether a "current product focus receipt" (Decision/Now/Why-now/Evidence/Not-now/Cut-suspend/First-visible-proof/ Acceptance-gate/Kill-revisit-trigger/Owner/Review-date) and the work order it gates state a real, testable decision and a real agent launch — not planning-placeholder prose that sounds like an assignment but can't be proven. Use when deciding whether to launch an agent chain against a milestone or a stated "focus," when a work order lacks explicit input/output/owner/proof-gate, or when an acceptance gate would only prove a cached UI state instead of daemon truth. NOT for distinguishing roadmap items from energy-driven sidequests (legible-roadmap-with-sidequests), reviewing a PRD/prototype for product-completeness gaps like cold start or pricing (product-reality-reviewer), or accepting already-finished work against a personal acceptance bar (port-daddy-user-surrogate-pm-review).

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Operations, debugging, and optimization for DAG workflows. Performs root cause analysis on failures, profiles execution performance, aggregates results from parallel branches, bridges context between nodes, and learns patterns from execution history. Activate on "DAG failed", "why did it fail", "root cause", "performance profile", "aggregate results", "merge branches", "execution patterns", "optimize DAG". NOT for planning DAGs (use dag-planner), executing DAGs (use dag-runtime), or validating outputs (use dag-quality).

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Design and validate versioned DAGs with typed dependencies, gates, and evidence-bound readiness. NOT for executing a DAG, granting work authority, or treating an unverified gate as cleared.

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Investigates DAG incidents with a precise top event, timeline, competing hypotheses, barriers, propagation, and bounded recovery. NOT for automated root-cause classification, trace collection, or performance profiling.

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Produce feasible non-preemptive DAG schedules from declared predecessors, durations, gates, capacities, and calendars. NOT for authorizing task execution or hiding resource and calendar infeasibility.

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Design RL simulation sandboxes, trajectory datasets, QLoRA/LoRA adaptation plans, eval harnesses, and rollback unhooks for agents learning specific coding behaviors beyond the base model. Use when building or reviewing tool-use training loops, offline trajectories, reward functions, self-improvement harnesses, or Port Daddy agent behavior curricula. NOT for generic ML tutorials, full model training operations, or production deployment without eval gates and safety unhooks.

日本語の概要は準備中です。原文の説明を表示しています。