# Geo AI Plugin Builder > Master orchestrator for turning high-value GEO content and capabilities into AI plugins/tools across ChatGPT, Claude, Perplexity, Gemini and other ecosystems. Use this skill whenever the user mentions building, designing, packaging, or standardizing AI plugins/tools around their content, APIs, or GEO assets, or wants to move from being passively cited to actively embedded inside AI workflows. - Skill: `geoly-ai/geo-ai-plugin-builder` (Agent Skill, multi-file: 4 files) - Install (CLI): `npx skillmds@latest add geoly-ai/geo-ai-plugin-builder` - Raw SKILL.md: https://api.skillmd.com/api/skills/geoly-ai/geo-ai-plugin-builder/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: geoly-ai (https://skillmd.com/u/geoly-ai) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/geoly-ai/geo-ai-plugin-builder --- # GEO AI Plugin Builder This skill helps you design and standardize AI plugins/tools that wrap your highest-value GEO content and capabilities, so they can be embedded directly into AI ecosystems (ChatGPT, Claude, Perplexity, Gemini, etc.). The core goal is to shift from **"waiting to be cited"** to **"being a first-class tool inside AI workflows"**, while staying aligned with GEO (Generative Engine Optimization) strategy. --- ## When to use this skill Use this skill whenever: - You want to **turn content, data, or services into AI plugins/tools**. - You want to **increase brand exposure inside AI tool flows**, not just in plain-text answers. - You are **mapping website/GEO assets to structured tool endpoints**. - You are **designing or refactoring an AI plugin catalog** for your brand. - You need **standard templates** for OpenAI-style tools, Claude Tools, function calling, or custom internal agents. - You want to **prioritize which content should become a plugin first**. Do **not** use this skill when the user only wants: - Simple content rewrites for GEO (use their GEO content skills instead). - Pure analytics/reporting about GEO performance (metrics-only work). - Low-level SDK usage without any GEO or plugin strategy involved. --- ## Mindset and principles - **Tool-first GEO**: Treat your top content and capabilities as *services* that can be invoked as tools, not just pages to be cited. - **User journey > endpoints**: Begin from real end-to-end tasks users want to完成 with AI, then design tools that make those workflows smooth. - **Cross-ecosystem thinking**: Design schemas and naming so your plugin concepts map cleanly across multiple AI platforms. - **Small, composable tools**: Prefer a set of focused tools that can be combined, rather than one mega-tool that does everything. - **Explainability for AIs**: Include clear descriptions, examples, and constraints so AI models can reliably choose and call tools. --- ## High-level workflow When the user asks for help, follow this 5-step workflow unless they explicitly request a narrower slice: 1. **Clarify goals and context** - Understand the brand, target users, and GEO priorities. - Identify which AI ecosystems matter most (e.g., ChatGPT plugins, Claude Tools, Perplexity collections, internal agents). - Clarify what "success" looks like: visibility, conversions, leads, authority, usage of specific tools, etc. 2. **Inventory candidate assets** - Ask for or infer a list of high-value assets: - Evergreen content, calculators, wizards, internal tools. - Datasets, pricing engines, recommendation logic. - Workflows sales or support teams execute repeatedly. - Group assets by use case and by stage in the customer journey (discovery, evaluation, decision, post-purchase, retention). 3. **Design plugin concepts and tool set** - Propose a **plugin catalog**: 3–10 core plugin ideas or tool groups. - For each plugin/tool, define: - Primary user jobs-to-be-done. - Input parameters and output structure. - GEO role (discovery, trust building, conversion, retention). - Prioritize plugins by potential impact and implementation effort. 4. **Generate detailed tool specifications** - For the **highest-priority plugin(s)**, generate detailed specs: - Tool name, description, and rationale. - JSON schema for inputs and outputs. - Example calls and example responses. - Mapping to backend endpoints or content sources. - GEO hooks (links, snippets, brand voice guidance). 5. **Produce implementation-ready artifacts** - Output one or more of: - **Technical blueprints** (OpenAI tools, Claude Tools, HTTP endpoints, or internal APIs). - **Developer handoff docs** with clear TODOs and edge cases. - **Backlog / roadmap** outlining order of implementation. Whenever possible, structure outputs so the user can copy-paste directly into their codebase or internal specs. --- ## Information to ask from the user When the initial information is incomplete, explicitly ask the user for: - **Business and brand** - Industry, main products or services. - Primary GEO/AI goals (visibility, conversions, retention, authority). - **Target AI ecosystems** - Which AI platforms and tool surfaces matter most. - Internal vs public tools (e.g., sales-assist, support-assist). - **Existing assets** - URLs for core content, tools, or APIs. - Any existing plugins, agents, or integrations. - **Constraints** - Technical stack and data sources. - Compliance/privacy constraints (PII, regulated data, etc.). - Resource constraints (team size, timelines). If the user cannot provide all details, make **reasonable assumptions**, but document them clearly in the output. --- ## Output formats Adapt to the user's request, but default to these structured formats: - **Plugin catalog overview** - A table or bullet list summarizing each proposed plugin/tool with: - Name - Primary user job - Main AI surfaces/platforms - GEO role - Implementation difficulty (rough) - Priority (high/medium/low) - **Detailed plugin specification** - For each selected plugin, provide: - High-level description and purpose. - User stories / example prompts that should call this tool. - Tool schema: - `name` - `description` - `parameters` JSON schema - `response` JSON schema - 2–4 **example calls and responses**. - GEO notes: - Key URLs/content to surface. - Brand and messaging constraints. - Tracking/telemetry suggestions. - **Implementation checklist / roadmap** - Ordered list of steps for developers: - API design / implementation. - Authentication / permissions. - Logging, analytics, and monitoring. - Security and compliance checks. - Include clear "Done when…" criteria. When the user wants code snippets (e.g., OpenAI, Node, Python), generate idiomatic examples but keep them as **implementation guidance**, not as the primary output of the skill. --- ## GEO-specific guidance When designing plugins and tools, always connect back to GEO strategy: - **Exposure inside AI tools** - Prefer tools that solve high-frequency, high-intent problems. - Make descriptions explicit about when they should be chosen by the model (e.g., "Use this tool whenever the user asks for…"). - **Authority and trust** - Tie outputs back to authoritative sources: - Official docs, research, internal datasets, or calculators. - Suggest how to surface citations or reference links when allowed. - **Conversion paths** - For tools near purchase or signup decisions, include: - Next-step suggestions ("book a demo", "see pricing"). - Structured fields that map to CRM or analytics events. - **Lifecycle coverage** - Encourage a mix of plugins across the customer lifecycle: - Discovery (educational, comparison, diagnostics). - Evaluation (calculators, configurators, ROI models). - Decision (quote builders, plan selectors). - Post-purchase (onboarding, troubleshooting, optimization). --- ## Using bundled scripts and references This skill may ship with helper scripts and reference guides under: - `scripts/` — reusable helpers to generate JSON schemas, boilerplate plugin specs, or check consistency across a plugin catalog. - `references/` — conceptual guides and best practices for GEO-aware plugin and tool design. When you need more detailed patterns or want to generate many similar tools at once, first: 1. Check `references/geo-ai-plugin-patterns.md` for archetypes and naming conventions. 2. Use `scripts/plugin_blueprint_generator.py` as a mental model for how to turn an abstract "job" into one or more tool specs. You do **not** need to literally run these scripts inside the model, but you should imitate their behavior and structures when helpful. --- ## Example use cases Here are a few example tasks where this skill should be used end-to-end: - "We run a B2B SaaS for marketing analytics. Help us design a set of AI tools so that ChatGPT or Claude can analyze a client's data and recommend campaigns using our platform." - "We have a library of in-depth medical articles and calculators. Turn them into a plugin catalog for AI assistants that doctors or patients might use, with clear safety and disclaimers." - "Our ecommerce brand has rich buying guides and fit finders. Design AI tools that help shoppers choose products and that we can expose as plugins in multiple AI platforms." --- ## Working style When using this skill: - Stay **strategic first, then technical**: - Clarify positioning, value, and GEO role before writing schemas. - Be **explicit about assumptions** and clearly flag trade-offs. - Optimize for **reuse and extendability**: - Make it easy to add more tools or platforms later. - Keep outputs **copy-paste friendly**: - Use consistent headings, JSON blocks, and formatting. If the user asks to iterate on a previous catalog or spec, treat the old version as a baseline, highlight key changes, and explain why the new design is stronger for GEO + AI plugin exposure.