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Prepare a game's launch day patch by selecting known bugs that are safe to fix quickly. Coordinate minimal fixes, verify affected areas, and document deferred issues, quality checks, rollback procedures, and patch notes.
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Prepare a deployment checklist covering tests, approvals, database changes, release steps, and monitoring. Tailor it to the release and document rollback triggers, the conditions for reverting a change, before production deployment begins.
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Rehearse Convex schema changes on a deployment seeded with a production snapshot. Populate existing records, verify data and behavior, then repeat the proven sequence in production with explicit approval, keeping the snapshot available for rollback.
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Enhancement overlay — version the WHOLE deployable LLM-app artifact as one bundle: prompts + compiled programs + model snapshot pins + retrieval config + eval-set version, versioned together so a deploy is reproducible and rollback is atomic. Activate when preparing to deploy an LLM app, when asking "what exactly is running in prod right now?", when a deploy must be reproducible months later, or when an incident needs a clean rollback. The core reframe: an LLM app artifact is NOT an ML model — it is a manifest over many independently-mutable parts, not one weights file. Do NOT activate for one-off prompt edits with no deploy, for a single-component demo, or where a vendor owns the whole prompt lifecycle. For versioning ONE compiled prompt use [[agentsop-per-model-artifacts]]; for the CI comparison mechanism use [[agentsop-regression-gate]]. Search keywords: prompt versioning, reproducible deploy, what is running in prod, rollback LLM app, model pinning, prompt registry, version prompts and config.
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Documents rollback procedures before making risky changes. Covers what's changing, verification steps, rollback procedures, and blast radius assessment. Use before database migrations, breaking API changes, infrastructure or DNS changes, large dependency upgrades, or any change where undo is not obvious.
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Use when planning, reviewing, or troubleshooting Salesforce metadata releases and admin deployment processes. Triggers: 'change set', 'deployment plan', 'rollback', 'DevOps Center', 'SFDX deploy', 'release checklist', 'production deployment', 'validation only deploy', 'quick deploy', 'test level', 'rollbackOnError', 'destructive changes', 'package.xml for an admin release', 'deployment status'. NOT for change set upload mechanics — use devops/change-set-deployment. NOT for scoring release risk up front — use admin/deployment-risk-assessment.
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Ensure design/ADR changes include a concrete migration plan, rollout strategy, rollback conditions, and compatibility considerations.
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Turn lessons from complex tasks, debugging, failures, or rollbacks into short learning entries. Capture the root cause, a reusable action, and a recognizable signal, then merge examples that share a cause with existing notes.
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Set up automated checks and deployment workflows with GitHub Actions. Covers tests, type checks, builds, security audits, preview deployments, staged releases, and rollback plans, with guidance for diagnosing failures and reducing pipeline runtime.
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Check code and agent outputs, track reliability scores, and roll back changes that fail a chosen threshold. Includes quality reports, live monitoring, and integration with automated build and deployment workflows.
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Control a running iTerm2 workspace from the command line. See what each terminal pane is doing, send commands, read current and past output, arrange windows and tabs, manage tmux integration, and change preferences.
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Control a running iTerm2 workspace from the command line. Inspect processes and directories across panes, send commands, read terminal history, arrange windows and tabs, and manage preferences or tmux integration.
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Plan AWS infrastructure changes by checking application requirements and existing configuration, then selecting guidance from an external skill collection. Produces a reviewable plan covering access permissions, networking, cost assumptions, validation, and rollback.
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Improve an existing AI agent by analyzing execution records, user feedback, and performance metrics. Refine prompts and workflows, compare original and revised versions through tests, and plan staged releases with monitoring and rollback when results worsen.
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Design machine learning workflows from data preparation through training, validation, deployment, and monitoring. Use templates and guidance to connect stages, track versions and experiments, handle failures, and plan gradual releases with rollback options.
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Helps plan and implement database structure changes and data transformations using Sequelize, TypeORM, or Prisma. Includes staged changes intended to avoid downtime, plus transaction and backup examples for rolling back failed migrations.
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Design CI/CD pipelines that move applications through development, staging, and production. Define approval and security checks, gradual release strategies, health checks, and rollback procedures, and investigate gates or deployments that fail to progress.
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Diagnose Fedora Linux problems with a structured troubleshooting plan. Get commands for checking services, logs, and packages, followed by remediation, validation, and rollback steps that account for SELinux and firewalld where relevant.
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Investigate Debian Linux issues through service checks, logs, and package tools. Receive repair commands, verification steps, and rollback guidance, with attention to AppArmor security restrictions or firewall settings when relevant.
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Diagnose CentOS problems using service status, logs, and RHEL-compatible commands. Get remediation commands, checks after major changes, and rollback steps, with attention to SELinux access controls and the firewalld firewall where relevant.
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Diagnose Arch Linux problems by reviewing recent updates, service logs, and packages. Get a step-by-step investigation plan, ready-to-copy repair commands, verification steps, and guidance for rollback or cleanup.
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Draft a pull request description from existing project records and verification results. Present the change with a compact visual, before-and-after evidence, rollback details, and its wider impact so reviewers can assess the work.
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Consolidate inconsistent gbrain page types into the standard gbrain-base-v2 classification. Preview proposed changes, convert redirect pages into aliases and relationship pages into links, then verify the migration with original type information retained for rollback.
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Turn plain language requirements into SQL, investigate slow queries, document database structures, and prepare migration templates with rollback plans. Support everyday database development and ORM use, where libraries connect application code to database tables.
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