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jaganpro/sf-diagram-nanobananapro

AI-powered image generation for Salesforce visuals via Nano Banana Pro. TRIGGER when: user asks for PNG/SVG output, UI mockups, wireframes, visual ERDs, or says "generate image" / "create mockup". DO NOT TRIGGER when: text-based Mermaid diagrams (use sf-diagram-mermaid), or non-visual documentation tasks.

Funciona com~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/jaganpro/sf-skills/tree/main/skills/sf-diagram-nanobananapro

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jaganpro/sf-diagram-nanobananapro

AI-powered image generation for Salesforce visuals via Nano Banana Pro. TRIGGER when: user asks for PNG/SVG output, UI mockups, wireframes, visual ERDs, or says "generate image" / "create mockup". DO NOT TRIGGER when: text-based Mermaid diagrams (use sf-diagram-mermaid), or non-visual documentation tasks.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

jaganpro/sf-ai-agentforce

Agentforce Builder metadata path for Builder-managed topics/actions, Prompt Builder templates, GenAiFunction/GenAiPlugin, Models API, and custom Lightning types. TRIGGER when: user maintains or configures Builder metadata agents, creates topics/actions, works with Prompt Builder templates, or touches .genAiFunction, .genAiPlugin, or .genAiPromptTemplate metadata XML files. DO NOT TRIGGER when: Agent Script DSL .agent files (use sf-ai-agentscript), agent testing (use sf-ai-agentforce-testing), or persona design (use sf-ai-agentforce-persona).

jaganpro/sf-ai-agentforce-observability

Agentforce session tracing extraction and analysis. TRIGGER when: user extracts STDM data from Data Cloud, analyzes agent session traces, debugs agent conversations via telemetry, or works with .parquet files from Agentforce. DO NOT TRIGGER when: testing agents (use sf-ai-agentforce-testing), Apex debug logs (use sf-debug), or building agents (use sf-ai-agentforce).

jaganpro/sf-ai-agentforce-persona

Deep persona design for Agentforce agents with 50-point scoring. TRIGGER when: user designs agent personas, defines agent personality/identity, creates persona documents, encodes persona into Agentforce Builder fields or Agent Script, translates brand guidelines to agent voice, or asks about agent tone/voice/register. DO NOT TRIGGER when: building agent metadata (use sf-ai-agentforce), testing agents (use sf-ai-agentforce-testing), or Agent Script DSL (use sf-ai-agentscript).

jaganpro/sf-ai-agentforce-testing

Agentforce agent testing with dual-track workflow and 100-point scoring. TRIGGER when: user tests Agentforce agents, runs sf agent test commands, creates test specs, validates topic routing, or analyzes agent test coverage. DO NOT TRIGGER when: Apex unit tests (use sf-testing), building agents (use sf-ai-agentforce), or Agent Script DSL (use sf-ai-agentscript).

jaganpro/sf-ai-agentscript

Agent Script DSL for deterministic Agentforce agents. TRIGGER when: user writes or edits .agent files, builds FSM-based agents, uses Agent Script CLI (sf agent generate authoring-bundle, sf agent validate authoring-bundle, sf agent preview, sf agent publish authoring-bundle, sf agent activate), or asks about deterministic agent patterns, slot filling, or instruction resolution. DO NOT TRIGGER when: Builder metadata work (use sf-ai-agentforce), agent testing (use sf-ai-agentforce-testing), or persona design (use sf-ai-agentforce-persona).

jaganpro/sf-apex

Generates and reviews Salesforce Apex code with 150-point scoring. TRIGGER when: user writes, reviews, or fixes Apex classes, triggers, test classes, batch/queueable/schedulable jobs, or touches .cls/.trigger files. DO NOT TRIGGER when: LWC JavaScript (use sf-lwc), Flow XML (use sf-flow), SOQL-only queries (use sf-soql), or non-Salesforce code.

jaganpro/sf-connected-apps

Salesforce Connected Apps and OAuth configuration with 120-point scoring. TRIGGER when: user configures OAuth flows, JWT bearer auth, Connected Apps, or touches .connectedApp-meta.xml / .eca-meta.xml files. DO NOT TRIGGER when: Named Credentials for callouts (use sf-integration), permission policies (use sf-permissions), or API endpoint code (use sf-apex).

jaganpro/sf-data

Salesforce data operations with 130-point scoring. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, or needs data factory patterns for Apex tests. DO NOT TRIGGER when: SOQL query writing only (use sf-soql), Apex test execution (use sf-testing), or metadata deployment (use sf-deploy).

jaganpro/sf-datacloud

Salesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).

jaganpro/sf-datacloud-act

Salesforce Data Cloud Act phase. TRIGGER when: user manages activations, activation targets, data actions, or downstream delivery of Data Cloud audiences and data. DO NOT TRIGGER when: the task is segment creation (use sf-datacloud-segment), data retrieval/search work (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).

jaganpro/sf-datacloud-connect

Salesforce Data Cloud Connect phase. TRIGGER when: user manages Data Cloud connections, connectors, connector metadata, tests a connection, browses source objects or databases, or sets up a new source system. DO NOT TRIGGER when: the task is about data streams or DLOs (use sf-datacloud-prepare), DMOs or identity resolution (use sf-datacloud-harmonize), retrieval/search (use sf-datacloud-retrieve), or STDM telemetry (use sf-ai-agentforce-observability).

jaganpro/sf-datacloud-harmonize

Salesforce Data Cloud Harmonize phase. TRIGGER when: user works with DMOs, mappings, relationships, identity resolution, unified profiles, data graphs, or universal IDs. DO NOT TRIGGER when: the task is only about streams/DLOs (use sf-datacloud-prepare), segments/insights (use sf-datacloud-segment), retrieval/search (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).

jaganpro/sf-datacloud-prepare

Salesforce Data Cloud Prepare phase. TRIGGER when: user creates or manages Data Cloud data streams, DLOs, transforms, or Document AI configurations, or asks about ingestion into Data Cloud. DO NOT TRIGGER when: the task is connection setup only (use sf-datacloud-connect), DMOs and identity resolution (use sf-datacloud-harmonize), or query/search work (use sf-datacloud-retrieve).

jaganpro/sf-datacloud-retrieve

Salesforce Data Cloud Retrieve phase. TRIGGER when: user runs Data Cloud SQL, describe, async queries, vector search, search-index workflows, or metadata introspection for Data Cloud objects. DO NOT TRIGGER when: the task is standard CRM SOQL (use sf-soql), segment creation or calculated insight design (use sf-datacloud-segment), or STDM/session tracing/parquet analysis (use sf-ai-agentforce-observability).

jaganpro/sf-datacloud-segment

Salesforce Data Cloud Segment phase. TRIGGER when: user creates or publishes segments, manages calculated insights, inspects segment counts or membership, or troubleshoots audience SQL in Data Cloud. DO NOT TRIGGER when: the task is DMO/mapping/identity-resolution work (use sf-datacloud-harmonize), activation work (use sf-datacloud-act), query/search-index work (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).

jaganpro/sf-debug

Salesforce debug log analysis and troubleshooting with 100-point scoring. TRIGGER when: user analyzes debug logs, hits governor limits, reads stack traces, or touches .log files from Salesforce orgs. DO NOT TRIGGER when: running Apex tests (use sf-testing), fixing Apex code (use sf-apex), or Agentforce session tracing (use sf-ai-agentforce-observability).

jaganpro/sf-deploy

Salesforce DevOps automation using sf CLI v2. TRIGGER when: user deploys metadata, creates/manages scratch orgs or sandboxes, sets up CI/CD pipelines, or troubleshoots deployment errors with sf project deploy. DO NOT TRIGGER when: writing Apex/LWC code (use sf-apex/sf-lwc), creating metadata XML (use sf-metadata), or querying org data (use sf-data).

jaganpro/sf-diagram-mermaid

Salesforce architecture diagrams using Mermaid with ASCII fallback. TRIGGER when: user says "diagram", "visualize", "ERD", or asks for sequence diagrams, flowcharts, class diagrams, or architecture visualizations in Mermaid. DO NOT TRIGGER when: user wants PNG/SVG image output (use sf-diagram-nanobananapro), or asks about non-Salesforce systems.

jaganpro/sf-docs

Official Salesforce documentation retrieval guidance. Use when you need authoritative Salesforce docs from developer.salesforce.com or help.salesforce.com, especially when pages are JS-heavy, shell-rendered, or hard to extract with naive fetching.

jaganpro/sf-flow

Creates and validates Salesforce Flows with 110-point scoring. TRIGGER when: user builds or edits record-triggered, screen, autolaunched, or scheduled flows, or touches .flow-meta.xml files. DO NOT TRIGGER when: Apex automation (use sf-apex), process builder migration questions only, or non-Flow declarative config (use sf-metadata).

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Create an end-to-end customer journey map with stages, touchpoints, emotions, pain points, and opportunities. Use when mapping the customer experience, identifying friction points, improving onboarding, or visualizing the user journey.

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tencentcloudbase/ai-model-wechat

Use this skill for WeChat Mini Program AI via wx.cloud.extend.AI (小程序, 企业微信小程序, wx.cloud apps). Features generateText and streamText with callbacks (onText, onEvent, onFinish). Models via wx.cloud.extend.AI.createModel with groups hunyuan-exp (小程序成长计划), cloudbase (main managed), or custom-*. Model IDs (deepseek-v4-flash, deepseek-v3.2, hunyuan-2.0-instruct-20251111, glm-5, kimi-k2.6) go in the data wrapper model field. API differs from JS/Node SDK — streamText needs data wrapper, generateText returns raw response. MUST run two-step preflight before code — see body. Keywords: Mini Program AI, wx.cloud.extend.AI, 小程序成长计划, ai_miniprogram_inspire_plan, Token Credits 资源包, generateText, streamText, createModel, hunyuan-exp, TokenHub, Hunyuan, DeepSeek, GLM, Kimi, MiniMax. NOT for browser/Web (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation (use ai-model-nodejs).

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agricidaniel/seo-image-gen

AI image generation for SEO assets: OG/social preview images, blog hero images, schema images, product photography, infographics. Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says "generate image", "OG image", "social preview", "hero image", "blog image", "product photo", "infographic", "seo image", "create visual", "image-gen", "favicon", "schema image", "pinterest pin", "generate visual", "banner", or "thumbnail".

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doany-ai/image-edit

Edit images on RunComfy — this skill is a smart router that matches the user's intent to the right edit model in the RunComfy catalog. Picks Nano Banana Edit (batch up to 20, identity-preserving default), OpenAI GPT Image 2 Edit (multilingual in-image text rewrite, multi-ref composition, layout precision), Flux Kontext Pro (single-ref high-fidelity local edit), or Z-Image Turbo Inpaint (mask-driven precise region edit). Bundles each model's documented prompting patterns so the skill gets sharper edits without burning iterations on the wrong model. Calls `runcomfy run <vendor>/<model>/edit` through the local RunComfy CLI. Triggers on "image edit", "edit image", "image-to-image", "i2i", "swap background", "remove object", "rewrite headline", or any explicit ask to edit a single or batch of images.

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openai/spreadsheet

Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) with formula-aware workflows, cached recalculation, and visual review.

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End-to-end credit risk modeling workflow for application, behavior, collection, and anti-fraud risk models. Use when building, validating, comparing, or documenting scorecards, logistic regression, LightGBM, XGBoost/CatBoost/random forest, or other machine-learning credit models; when computing IV/WOE, KS, AUC, PSI, lift, score bands, OOT validation, feature importance, scorecard points, reject/approval strategies, or model development validation reports.

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