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概要と使いどころ
Analyze packaging configurations for carton size selection, void fill minimization, palletization efficiency, sustainable materials, and total packaging cost reduction aligned with ISTA and ASTM D4169 standards..
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Analyzes asset lifecycle planning systems for capital expenditure forecasting, replacement scheduling, total cost of ownership modeling, depreciation tracking, and facility condition assessments using IFMA standards and Facility Condition Index scoring..
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Analyze consumer modeling systems for purchase prediction, lifetime value estimation, multi-touch attribution, brand affinity, and switching cost analysis. Triggers: 'evaluate CLV model', 'review purchase prediction', 'audit attribution model', 'assess customer lifetime value'.
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Write SEO-optimized long-form articles targeting specific keywords using the They Ask You Answer Big 5 framework (Marcus Sheridan). Articles are categorized by Big 5 type (Cost, Problems, Versus, Best/Reviews, How-To) and structured accordingly. The "answer first" rule applies to every article. Use when the user asks for an SEO article, blog post for ranking, "rank for keyword X", organic content, search-optimized post, pillar page, or content for organic traffic. Includes keyword targeting, search intent matching, internal linking suggestions, and meta tags. For improving an existing article, see copy-review. For deciding what to write about, see social-calendar pillars and icp-research. For repurposing it, see content-repurposer.
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Use when the user says "map out our business model", "business model canvas", "how does our business work", "what are our key resources", "define our value proposition", "revenue model design", "cost structure", "who are our key partners", "lean canvas", "business model design", "how do we make money", or wants to document, stress-test, or redesign how [your startup] creates, delivers, and captures value.
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Analyze budget vs. actual variances, identify root causes, and recommend corrective actions. Use when an accountant or finance professional says "explain this variance", "budget vs. actual analysis", "why did we miss budget", "favorable / unfavorable variance", "price volume variance", "management reporting commentary", "explain the P&L variance to the CFO", "what drove the cost overrun", "revenue shortfall analysis", or needs to write the narrative behind a financial result. Also trigger when someone shares a table of actuals vs. budget and needs to explain the gaps - even if they don't use the word "variance".
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The art-route layer of the Forge skills. route_media.py is the one command that generates an image or an image-to-video clip - through the paid API of any provider whose key is configured (OpenAI, Google Gemini, xAI, BytePlus ModelArk, fal.ai; the configured key is the owner's consent), else through the user's own signed-in Codex or Grok CLI - and prints one JSON line with the route, artifact, sha256 and cost estimate; with no route it answers no-route (codeart2d is then the last resort). Also the capability check (forge_doctor), API key configuration, the spend ledger, resume and Codex image adoption. Use when a Forge skill sends a generation here, for the capability check, or when the user asks about keys, routes or spend. Not for planning, processing or QA of sprites, video frames or maps (generate2dsprite, video2dsprite, generate2dmap) or for code-drawn art (codeart2d).
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Run a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.
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Manage persistent coding sessions across Claude Code, Codex, Antigravity (agy), Grok Build, and OpenCode engines. Use when orchestrating multi-engine coding agents, starting/sending/stopping sessions, running multi-agent council collaborations, cross-session messaging, ultraplan deep planning, ultrareview parallel code review, autoloop autonomous workspace iteration, ultraapp building deployable web apps from a structured Q&A interview, switching models/tools at runtime, exposing the orchestrator's 78 tools as an MCP server to Hermes Agent / Claude Desktop / Cursor / Cline / Continue / Zed / Windsurf / Goose, or running as an Agent Client Protocol (ACP) agent that Zed / JetBrains / Neovim / Emacs / VS Code / dsh can drive directly. Triggers on "start a session", "send to session", "run council", "ultraplan", "ultrareview", "autoloop", "ultraapp", "Forge tab", "build a web app", "one-click app", "AppSpec", "autonomous iteration", "iterate until goal", "auto research", "switch model", "hand off a session", "session handoff", "switch engine", "continue on codex", "continue on claude", "move this session to another engine", "multi-agent coding", "coding session", "session inbox", "grok session", "grok build", "opencode", "mcp server", "clawo-mcp", "hermes mcp", "model context protocol", "ultracode", "dynamic workflow", "fanout", "fan-out", "best-of-N", "steer turn", "interrupt turn", "fork thread", "rollback turns", "acp", "agent client protocol", "clawo acp", "zed agent", "jetbrains agent", "external agent", "dsh subagent", "deepseek harness", "clawo runs", "run ledger", "session cost", "coding-agent token usage", "spend cap", "budget limit", "maxBudgetUsd", "durable workflow", "resume a run", "verify a coding run", "acceptance contract", "evidence bundle", "did the agent's tests actually pass", "protected tests", "agent edited the tests", "human gate", "repair loop", "clawo workflow", "clawo verify", "clawo solve", "clawo fanout", "fix and verify", "solve from the terminal".
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Plans and configures multi-tenancy on GKE. Covers namespace isolation, RBAC planning for teams, resource quotas, LimitRanges, network isolation, and cost allocation. Use when designing GKE multi-tenancy, configuring GKE namespaces, setting up resource quotas, or isolating GKE teams. Don't use for single-tenant cluster configuration or general deployment instructions (use gke-basics or gke-app-onboarding instead).
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Inspects Google Cloud Filestore capacity and utilization, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory), or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes.
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Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs (including cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don't use for generic VM management or non-observability tasks.
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Stores, retrieves, and manages data as objects in Cloud Storage (Google Cloud Storage, or GCS) buckets. Use when you need to interact with Cloud Storage — create or configure buckets, upload, download, stream, or transfer data, organize objects with folders, generate signed URLs, control access (IAM, ACLs, public access prevention), set storage classes and tiering (Standard, Nearline, Coldline, Archive), manage cost and lifecycle, protect data (versioning, encryption/CMEK, retention and Bucket Lock, object holds, soft delete), host static websites, trigger Pub/Sub notifications on object changes, mount buckets as a file system (gcsfuse), or optimize storage performance at any scale. Covers the gcloud storage / gsutil CLI, JSON and XML APIs, client libraries, Terraform, and Cloud Storage MCP servers. Don't use for block storage (Persistent Disk), data warehousing/analytics (BigQuery), or databases (Cloud SQL, Spanner, Bigtable, Firestore).
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Orchestrates comprehensive production readiness reviews and assessments for GKE clusters and workloads across scalability, security, reliability, observability, backup/DR, and cost optimization. Use when asked to productionize, prepare, assess, audit, or review a GKE cluster or workload before going live to production. Don't use for deep-dive single-domain implementation (use specific domain skills like gke-workload-scaling, gke-platform-security, gke-workload-security, gke-service-networking, gke-reliability instead).
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Creates Cloud Storage (Google Cloud Storage, or GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.
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。
Wire the current repository through the Caveman Cloud gateway so every LLM request is measured — cost, tokens, latency — with zero behavior change. Use when the user pastes the Caveman setup prompt, says "set up caveman", or wants LLM spend observability added to an app. Requires the gateway URL and a Cave API key (the setup prompt carries both).
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Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for public Vertex AI deployments (use the `vertex-deploy` skill) or for running model evaluations (use the `agent-platform-eval-flywheel` skill).
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。
Pre-production security checklist for Agentforce deployments: agent run-as permission scope, grounding-source data classification, action write-scope, audit trail. NOT for the full go-live readiness gate covering cost telemetry, rate limits, rollout and rollback — use agentforce/agentforce-production-readiness-checklist. NOT for a general org security review — use security/security-health-check.
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Cross-tool decision matrix for field-update automation in Salesforce — Before-Save Flow vs After-Save Flow vs Apex Trigger vs the deprecated Workflow Rule + Field Update. Covers the recursion / re-entrancy rules, governor cost per pattern (Before-Save flow is governor-free for the same record), the order-of-execution slot each tool occupies, and the Workflow-Rule-to-Flow migration playbook for field-update actions. NOT for the full record-save order of execution — use apex/order-of-execution-deep-dive. NOT for building the record-triggered Flow once the tool is chosen — use flow/record-triggered-flow-patterns. Trigger keywords: WorkflowFieldUpdate, reevaluateOnChange, onCreateOrTriggeringUpdate, doesRequireRecordChangedToMeetCriteria, failedMigrationToolVersion, Migrate to Flow, workflow-meta.xml, field update deprecated, double writer, second trigger pass.
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Usage-based pricing in Revenue Cloud: metered billing, usage records, rating, tiering, consumption schedules. NOT for choosing a CPQ pricing method (List, Block, Cost Plus Markup, Percent of Total) - use admin/pricing-model-design. NOT for legacy Salesforce Billing (blng__) schedules and invoice runs - use admin/billing-schedule-setup.
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Canonical go-live checklist for Agentforce deployments with rehearsed rollback and stakeholder sign-off records. NOT for the technical pre-prod verification behind those sign-off rows — cost telemetry, rate limits, canary rollout, latency benchmarks — use agentforce/agentforce-production-readiness-checklist. NOT for general Salesforce release management — use devops/release-management.
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Build the executive KPI dashboard for Agentforce: adoption, deflection, latency, cost, quality — KPI definitions, data sources, CRM Analytics lenses, alert thresholds. NOT for the platform's own session tracing, Agent Analytics and health monitoring — use agentforce/agentforce-observability. NOT for scoring agent answer quality offline — use agentforce/agentforce-eval-harness.
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Use when designing deployable Salesforce configuration with Custom Metadata Types, especially when choosing between CMTs, Custom Settings, and Custom Objects, protecting packaged defaults, or exposing config to Apex, Flow, and formulas. Triggers: 'custom metadata vs custom settings', 'deployable config', 'protected custom metadata', 'feature flags in Salesforce'. NOT for hierarchical Custom Settings resolution, getInstance/getValues, or their SOQL cost — use admin/custom-metadata-types-and-settings. NOT for high-churn transactional or user-managed business records — use admin/object-creation-and-design. NOT for secrets — use integration/named-credentials-setup. More trigger keywords: __mdt, CustomMetadata .md file, customMetadata folder, getInstance, getAll, xsi:type, visibility PackageProtected, MetadataRelationship, EntityDefinition field, $CustomMetadata.
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Designing Campaign Hierarchy for program-level ROI tracking, configuring Customizable Campaign Influence (CCI) attribution models, and interpreting multi-touch attribution from MCAE B2B Marketing Analytics. Trigger keywords: campaign ROI, attribution model, campaign hierarchy, first-touch, last-touch, multi-touch, CCI, campaign influence, revenue attribution, campaign member status. NOT for deciding which attribution model and KPIs to adopt before any config - use admin/marketing-reporting-requirements. NOT for MCAE connector setup or the campaign sync that writes Campaign Member records - use admin/mcae-pardot-setup. Also covers: CampaignSettings, enableCampaignInfluence2, enableAutoCampInfluenceDisabled, enableB2bmaCampaignInfluence2, enableAccountsAsCM, CampaignInfluenceModel metadata, isDefaultModel, isModelLocked, recordPreference, AllRecords, RecordsWithAttribution, CampaignInfluence.RevenueShare, ModelType, CampaignMemberStatus IsDefault HasResponded SortOrder, HierarchyActualCost, HierarchyAmountWonOpportunities, TotalNumberofResponses, Opportunity.CampaignId primary campaign source.
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。