4.5천건 · 관련도순
Audit and update metadata across multiple AEM Edge Delivery Services pages. Scans pages via the query index, identifies missing or inconsistent metadata (titles, descriptions, og tags, robots), and generates a corrected bulk metadata spreadsheet. Use when standardizing metadata across a site, preparing for launch, or fixing SEO issues at scale.
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Review code for AEM Edge Delivery Services projects. Use at the end of development (before PR) for self-review, or to review pull requests. Validates code quality, performance, accessibility, and adherence to EDS best practices.
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Survey available blocks from local AEM Edge Delivery Services project and Block Collection to understand the block palette available for authoring. Returns block inventory with purposes to inform content modeling decisions.
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Set up CI/CD pipelines for Adobe App Builder projects. Generates GitHub Actions workflows using adobe/aio-cli-setup-action@3 and adobe/aio-apps-action@3.3.0, plus patterns for Azure DevOps and GitLab CI. Handles OAuth S2S secrets injection, multi-workspace promotion (stage → prod), deploy gating with manifest validation. Use this skill whenever the user mentions CI/CD for App Builder, GitHub Actions for aio deploy, automated deployment pipelines, continuous integration, continuous delivery, deploy automation, multi-environment promotion, aio app add ci, or wants to automate their App Builder build and release process. Also trigger when users mention deploy workflows, release pipelines, or GitHub secrets for App Builder.
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Analyzes development requirements and generates structured acceptance criteria for AEM Edge Delivery Services (EDS) tasks. Use when the user needs to define acceptance criteria, write requirements, scope work, or create a definition of done for EDS blocks, components, variants, bug fixes, or styling changes. Produces task breakdowns, identifies edge cases, and documents analysis for new blocks, variants, behavior modifications, CSS-only changes, and bug fixes.
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Analyze content sequences and determine authoring approach (default content vs blocks). Validates block selection and section styling for import/migration to AEM Edge Delivery Services.
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Audit an AEM Edge Delivery Services page for content quality, SEO, accessibility, performance, and EDS best practices. Produces a prioritized fix list with specific remediation steps. Use when reviewing page quality, preparing for launch, or optimizing existing content.
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Obtains a valid Adobe IMS access token for the DA (Document Authoring) API. Use this skill as a prerequisite step whenever another skill needs to call admin.da.live — for example, before pushing HTML content, listing documents, or triggering a DA preview. Do NOT use this skill if you already have a valid DA_TOKEN in scope from a previous step in the same session.
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Prepare safe production launches — pre-launch checklist, monitoring, staged rollout, and rollback. Load when deploying to production, releasing a major change, opening beta access, or the user asks for a launch checklist, go-live plan, rollout strategy, or rollback plan. Not for local-only prototypes. Pairs with ci-cd-and-automation and app-security-hardening.
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Decompose multi-step work into a revisable subgoal plan with stable step IDs, checkpointing, and plan-ahead execution. Load when a task needs explicit planning before action, subgoal decomposition, plan checkpointing, or ReCAP-style plan-ahead execution. Also triggers on "structured plan", "plan with steps", "subgoal graph", "revise the plan", "checkpoint plan", or multi-step tasks where naive one-shot execution would be fragile. Skips trivial single-step tasks. Pairs with dynamic-routing on failure. Distinct from process-decomposer (registry/triage) and problem-to-plan (doc deliverables).
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Decompose tasks into structured, outcome-defined process entries with complexity triage. Load when user says "decompose this", "break this down", "what steps do I need", "plan this out", "what's the process for", "how do I approach this", or when any complex task needs structured execution planning. Includes a problem-understanding pass before complexity triage. Routes to `problem-to-plan` when the user needs planning deliverables (spec + plan + TODO). Does NOT replace brainstorming — brainstorming is design approval (upstream), this is execution planning (downstream).
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Deliver multi-file changes in thin vertical slices — implement, test, verify, commit, repeat. Load when implementing a feature from a plan, building across more than one file, refactoring, or when tempted to land a large change in one pass. Also triggers on "incremental implementation", "vertical slice", "thin slice", "one slice at a time", "don't do it all at once". Routes single-file fixes to direct execution. Pairs with test-driven-development and git-workflow-and-versioning.
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Append structured execution traces across operational, cognitive, and contextual surfaces with minimal overhead. Load when inspecting agent runs, logging tool calls and observations, enabling post-run debugging, or pairing with structured-planning step IDs. Also triggers on "trace this run", "log execution", "agent observability", "run log", or when fault-localize needs evidence. Default-on during multi-step plans. Traces live at .agent-loom/traces/ — git-ignored by default.
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Structure git work with atomic commits, conventional messages, short-lived branches, and pre-commit hygiene. Load when committing, branching, resolving merge conflicts, organizing parallel work, or reviewing git history. Also triggers on "git workflow", "commit message", "conventional commits", "atomic commit", "branch strategy", "git worktree", "how should I commit this". Does not replace project-specific hook policies — complements them.
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Save a Prisma Composer app to GitHub, connect its existing Prisma project, and enable or diagnose default-branch automatic deployments. Use when the user accepts the offer to save their code to GitHub and connect it to Prisma for automatic updates, accepts the shorter GitHub-saving offer, or directly requests this setup, including resuming an interrupted connection. Do not start GitHub setup for an ordinary build/deploy request, unrelated Git work, or a request to deploy an app before a live target has been established.
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Sync the live ~/.claude global config (settings.json, CLAUDE.md, statusline.ts, own skills, skills.sh lock file) into this git backup repo, then commit. Allowlist-based so credentials, history, and project transcripts are never copied. Use when the user says "sync my claude config", "back up .claude", "update the .claude repo", or runs "/sync-claude".
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Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the link", or "Push this live". No authentication required - returns preview URL and claimable deployment link.
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Search real-time news with bias scoring, get live stock/ETF/crypto data with AI analysis, ML options pricing, balanced news synthesis, and meme search via the Helium MCP server.
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Orchestrate end-to-end backend feature development from requirements to deployment. Use when coordinating multi-phase feature delivery across teams and services.
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Build real-time web applications with Azure Web PubSub SDK for Java. Use when implementing WebSocket-based messaging, live updates, chat applications, or server-to-client push notifications.
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Build real-time voice AI applications with bidirectional WebSocket communication.
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Orchestrate multiple Antigravity skills through guided workflows for SaaS MVP delivery, security audits, AI agent builds, and browser QA.
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Predict B-cell and T-cell epitopes for vaccine antigen design and epitope mapping with BepiPred-3.0, DiscoTope-3.0, the IEDB tools, and EL-mode MHC presentation. Encodes the load-bearing asymmetry that T-cell epitope prediction is mature (it reduces to MHC presentation, AUC>0.9) while B-cell prediction is unreliable (linear predictors ~AUC 0.6 because ~90% of real epitopes are conformational) — so structure-based DiscoTope-3.0 on AlphaFold models is the only defensible B-cell path, propensity scales are obsolete, and NetChop is largely redundant on EL-trained models. Use when mapping epitopes or selecting vaccine antigens. MHC binding lives in mhc-binding-prediction.
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Infer or annotate TCR antigen specificity by unsupervised clustering (TCRdist/tcrdist3, GLIPH2, clusTCR, GIANA) and database lookup (VDJdb, IEDB, McPAS-TCR), and rank candidates with supervised predictors (ERGO-II, NetTCR-2.x, pMTnet) under explicit caveats. Encodes the central truth that general TCR-epitope prediction for UNSEEN epitopes essentially does not work (collapses to near-random; IMMREP22, Grazioli 2022) because labeled data is dominated by a few immunodominant epitopes and there is no true negative set — so clustering for discovery is the honest task and de-novo binding needs wet-lab validation. Use when annotating TCR specificity or grouping a repertoire. Epitope/MHC context lives in mhc-binding-prediction.
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