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Use when an ISV or consulting partner is creating, pricing, publishing, or maintaining an AgentExchange listing through the Partner Console — covers the listing plan, the 5-step Listing Builder workflow (Fill in the Basics, Set Pricing, Add Details, Link Your Solution, Grow Your Business), commercialization models (revenue share vs. annual fee vs. freemium), AgentExchange Checkout setup (Stripe connection, pricing plans, fees, geographic eligibility), Private Offers, Security Review gating, and post-publish listing updates. NOT for building the agent or managed package itself (use agentforce/agentforce-agent-creation and devops/second-generation-managed-packages), NOT for LMA/Trialforce licensing internals (use devops/isv-license-management-and-trialforce), and NOT for the customer-side install experience.

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Use this skill to define and validate the requirements for a Salesforce Partner Relationship Management (PRM) implementation: deal registration flows, lead distribution models, partner tier hierarchies, MDF budget tracking, and co-marketing content entitlement. Trigger keywords: partner community requirements, PRM deal registration setup, channel partner portal requirements, lead distribution partner, partner tier management, MDF tracking, co-marketing entitlement. NOT for implementing the partner sharing model — use data/partner-data-access-patterns. NOT for building the portal in Experience Builder — use admin/experience-cloud-site-setup. More trigger keywords: partner portal design worksheet, partner tier licence and role depth, PartnerAccountId blank on opportunity, portal role Executive Manager User, sharing set does not support Lead, enable partner user greyed out, offboard a partner firm, PartnerMarketingBudget PartnerFundRequest PartnerFundClaim, ChannelProgramLevel partner tier, deal registration acceptance step.

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Use when designing or maintaining the role hierarchy as a record-access mechanism. Trigger keywords: role hierarchy, manager cannot see subordinate records, grant access using hierarchies, role reparenting, portal role, how deep should the role hierarchy be, design the role hierarchy. NOT for territory models - use admin/enterprise-territory-management. NOT for rule-based grants - use admin/sharing-rules. NOT for the overall model - use admin/sharing-and-visibility.

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Use this skill when configuring MCAE (Account Engagement / Pardot) lead scoring models, grading profiles, score decay rules, or automation rules that fire on score/grade thresholds. Covers: scoring point values per activity, score decay for inactivity, Profiles for fit grading, combined MQL definitions (Score + Grade), and automation rules vs completion actions. NOT for defining the MQL model before build — use admin/lead-scoring-requirements. NOT for Engagement Studio nurture programs — use admin/lead-nurture-journey-design.

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Gathering and documenting Salesforce marketing reporting requirements: defining KPIs, choosing an attribution model (First Touch / Last Touch / Even Distribution / Multi-Touch), selecting the right Campaign Influence configuration, and mapping business questions to report types and dashboard features. NOT for actually building the Campaign Hierarchy and CCI models - use admin/campaign-planning-and-attribution. NOT for CRM Analytics dataset and dashboard requirements - use admin/analytics-requirements-gathering.

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Use when configuring or troubleshooting Salesforce Enterprise Territory Management (ETM): territory models, territory types, territory hierarchies, account assignment rules, opportunity territory assignment, and forecast by territory. Trigger keywords: territory model, territory hierarchy, ETM, assign accounts to territories, territory forecast, territory activation. NOT for choosing the coverage model first — use admin/territory-design-requirements. NOT for role hierarchy — use admin/sharing-and-visibility. NOT for Field Service ServiceTerritory — use admin/fsl-service-territory-setup. Trigger keywords: Territory2, Territory2Model, Territory2Rule, territory2Model-meta.xml, ObjectTerritory2Association, UserTerritory2Association, territory assignment rule, run assignment rules, territory access level, Manage Territories permission.

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Configure FSL Shifts, ShiftTemplates, ShiftPatterns, and Crew ServiceResources — availability windows layered on Operating Hours, bulk shift generation via ShiftPattern + ShiftPatternEntry, and the two Crew models (Static vs. Shell/Dynamic). NOT for setting up the resources themselves — types, skills, ResourcePreference — use admin/fsl-resource-management. NOT for capping how many hours or appointments a resource can take — use admin/fsl-capacity-planning.

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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.

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Deep learning framework development with tinygrad - a minimal tensor library with autograd, JIT compilation, and multi-device support. Use when writing neural networks, training models, implementing tensor operations, working with UOps/PatternMatcher for graph transformations, or contributing to tinygrad internals. Triggers on tinygrad imports, Tensor operations, nn modules, optimizer usage, schedule/codegen work, or device backends.

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Climate science expert explaining climate systems, climate change, models, and environmental impacts

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The model-generator shape for Skmtc: one definition per component schema, built by copying the shipped SKELETON package and filling its SLOT markers with the target library's syntax. Covers the edge cases every model generator must survive — refs, recursion, optional vs nullable, additionalProperties, enums, readOnly/writeOnly. Use when authoring or editing a generator that maps schemas to a validator/schema/type library ("write a gen-<lib>", "map OpenAPI models to <lib>"). Load ALONGSIDE skmtc-generator (engine rules) and skmtc-lang-typescript (TS layer).

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Retrospective learning from a completed experience. Takes a project, incident, decision that played out, or time period; gathers ground truth (observations) separately from recollections; spawns reflectors applying different lenses (what-worked-vs-got-lucky, what-didn't, what-surprised, system-rewards-vs-intent, decisions-that-aged, what-to-tell-past-self, patterns-that-recur) in isolation; synthesizes into updated mental models as first-class output. Produces feedback only — no code, no tickets, no artifacts.

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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.

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FastAPI patterns for async APIs, dependency injection, Pydantic request and response models, OpenAPI docs, tests, security, and production readiness.

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Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the animations", "audit the motion", "make this app feel better", or wants a roadmap of animation fixes rather than a review of a single diff.

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Generate images, videos, TTS, and music through Pixazo (one API key, 80+ models). Use when Decisions has a Pixazo key or the pixazo MCP is connected.

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Use Mermaid diagrams in DecisionsAI to explain technical topics — architecture, flows, sequences, and data models via the freestanding diagram viewer.

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AI-powered revenue intelligence: sales call insight extraction, content-to-revenue attribution, and multi-source client reporting. Use when asked to analyze sales calls, build revenue attribution models, or generate client reports.

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Resolve CodeRabbit review feedback on a GitHub pull request. Collects every open CodeRabbit finding (inline threads, plus the nitpick and outside-diff findings packed into review bodies), judges and fixes each one against the real code with subagents, unifies fixes that share a pattern, commits locally, asks before pushing, then shows every reply draft linked to its finding and posts only on approval. Runs only on top-tier models. Use on "resolve the CodeRabbit feedback", "address coderabbit comments", "answer the rabbit", "fix what CodeRabbit flagged on

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Turn clients into long-term revenue engines. This isn't advice — it's a complete operating system with scoring models, templates, playbooks, and automation patterns that work for any B2B or B2C sub...

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Complete community building, engagement, and monetization system. From zero to thriving community — launch strategy, member engagement loops, content programming, moderation frameworks, growth tactics, monetization models, and health metrics. Works for Discord, Slack, Telegram, Circle, forums, or any platform.

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Track AI visibility — measure whether a brand is mentioned and cited by AI assistants (Gemini, ChatGPT, Perplexity) for target prompts. Runs scans, tracks mention/citation rates over time, detects trends, and identifies opportunities. Uses Gemini API free tier (with grounding) as primary method, web search as fallback. Use when a user wants to: check if AI models mention their brand, track AI citation changes over time, measure AEO content effectiveness, monitor competitor AI visibility, or audit their brand's presence in AI-generated answers. Pairs with aeo-prompt-research-free (identifies prompts) and aeo-content-free (creates/refreshes content). This skill closes the loop by measuring results.

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Create or refresh AEO-optimized content that gets cited by AI assistants (Gemini, ChatGPT, Perplexity) using only free tools. Two modes: CREATE new content targeting a specific prompt, or REFRESH existing content to improve AI citation-worthiness. Researches what AI models currently cite, builds a competitive brief, and produces citation-worthy content. Use when a user wants to: write content optimized for AI citations, create articles that show up in AI answers, refresh/update existing content for better AI visibility, build authority content for answer engines, or produce AEO content without paid tools. No API keys required — uses web_fetch, web_search (free tier), and LLM reasoning only. Pairs with aeo-prompt-research-free (which identifies WHAT to write about; this skill handles HOW to write or refresh it).

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Analyze what search queries Gemini uses when answering a prompt, by running it multiple times with Google Search grounding and reporting frequency distribution. Use when investigating AEO query patterns, understanding how AI models search the web for a topic, or studying the probabilistic nature of AI-triggered search queries.

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