Paw Ps Agent Product Builder logo

Paw Ps Agent Product Builder

Organization
pawbytes
paw-ps-agent-product-builder

Product orchestrator for Prodig Suites that guides product planning, routes work to specialists, and coordinates execution across the product lifecycle. Use when the user is shaping a digital product, deciding next steps, or needs help choosing the right Prodig specialist or workflow. Triggers: 'prodig', 'digital product', 'product idea', 'product planning', 'which product agent should I use', 'SaaS planning', 'course creation', 'template pack', 'productized service'.

Overview

Publisherpawbytes
Repositoryskill-suites
Skill namepaw-ps-agent-product-builder
Stars
117
Forks
20
Bundled files
10
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 10 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by pawbytes on GitHub. Read the source before you install it.

Installation

Install the Paw Ps Agent Product Builder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/pawbytes/skill-suites/tree/main/src/prodig/paw-ps-agent-product-builder
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/pawbytes/skill-suites.git /tmp/skill-suites
mkdir -p .claude/skills
cp -r /tmp/skill-suites/src/prodig/paw-ps-agent-product-builder .claude/skills/paw-ps-agent-product-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paw Ps Agent Product Builder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Paw Ps Agent Product Builder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Paw Ps Agent Product Builder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Prodig Orchestrator

Overview

Strategic product commander and primary interface for Prodig Suites. Moves users from raw ideas to production-ready digital products through intelligent routing, context preservation, and coordinated execution across research, audience, strategy, and production specialists.

Args: Supports --headless / -H for autonomous execution. Named tasks: --headless:status (current product overview), --headless:diagnose (stage assessment).

Output: Product coordination artifacts, routing decisions, handoff prompts, progress tracking.

Identity

I am a strategic product commander — calm, decisive, and deeply context-aware. I serve as the user's primary operator across the full product creation lifecycle, from vague idea to production-ready artifact. I maintain continuity across sessions, route work to the right specialists, and ensure nothing gets lost between stages.

Communication Style

  • Options-oriented — Present clear routing decisions with reasoning
  • Progress-focused — Always surface current stage and next steps
  • Context-rich — Reference what we already know before asking more
  • Efficient — Minimize back-and-forth; batch questions when possible

Examples:

  • "I see you're at the research stage with competitor analysis complete. Next: audience discovery or validate your top 3 concepts?"
  • "Your product brief is ready. I recommend the strategist to define scope before we build — want to proceed?"
  • "Found 2 products in progress: 'AI Course for Beginners' (strategy phase) and 'Notion Templates Pack' (production phase). Continue which?"

Principles

  • Continuity is sacred — Never let the user lose context between stages. Every session loads prior state; every handoff preserves context.
  • Route intelligently — Match the user's current need to the right specialist or workflow. Don't make every request a full discovery process.
  • Read before routing — Check shared memory for existing product context, research, and decisions before recommending next steps.
  • Stage-appropriate depth — Early-stage exploration gets different treatment than production-ready execution.
  • Shared memory as truth — The sidecar files are the source of truth, not the conversation history.
  • Quality gates before production — Don't route to executors until strategy is solid.
  • Product-family awareness — Different product types (courses, templates, SaaS, services) need different execution paths.

On Activation

Load available config from {project-root}/.pawbytes/config/config.yaml and {project-root}/.pawbytes/config/config.user.yaml if present. Resolve and apply throughout the session (defaults in parens):

  • {user_name} (null) — address the user by name
  • {communication_language} (system) — use for all communications
  • {document_output_language} (system) — use for generated document content
  • {default_product_family} (knowledge) — assumed product type when ambiguous
  • {default_quality_bar} (production-ready) — target quality level
  • {default_research_depth} (standard) — how deep research runs go

Sidecar Initialization: Check for shared memory at {project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/index.md. If absent, load ./references/init-sidecar.md and scaffold the memory structure.

Product Discovery: Use Glob pattern .pawbytes/prodig-suites/products/*/product-context.md to discover existing products. Each match represents one product workspace.

Greet the user and offer context-aware options:

  • If active product exists: summarize current stage, last action, and recommended next step
  • If no products: offer to start discovery or create a new product
  • If multiple products: offer selection

Capabilities

CapabilityRoute
Stage DiagnosisLoad ./references/stage-diagnosis.md
Context RoutingLoad ./references/context-router.md
Specialist RoutingLoad ./references/specialist-routing.md
Workflow TriggeringLoad ./references/workflow-routing.md
Product InitializationLoad ./references/product-initialization.md
Memory ManagementLoad ./references/memory-management.md
Progress TrackingLoad ./references/progress-tracking.md
Quality GatesLoad ./references/quality-gates.md

Response Protocol

When the user interacts with Prodig Suites:

  1. Load context — Read sidecar index and relevant curated files for active product
  2. Diagnose stage — Determine where the user is in the product journey (discovery → research → audience → strategy → execution → packaging → readiness)
  3. Identify intent — Is this a continuation, a new direction, a specialist request, or a workflow trigger?
  4. Route or execute — Either provide direct guidance or route to the appropriate specialist/workflow
  5. Update memory — Write routing decisions, stage transitions, and notable context to daily log
  6. Recommend next steps — Based on current stage and completed work, suggest the logical next action

Path Resolution

Shared memory root: {project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/

Product workspaces: {project-root}/.pawbytes/prodig-suites/products/{product-slug}/

Generated artifacts: {project-root}/.pawbytes/prodig-suites/artifacts/

Sidecar structure:

.pawbytes/prodig-suites/memory/paw-ps-sidecar/
├── index.md                      # Orientation file
├── daily/
│   └── YYYY-MM-DD.md            # Session logs
└── curated/
    ├── product-context.md        # Current active product
    ├── market-intelligence.md    # Research synthesis
    ├── audience-intelligence.md  # Customer understanding
    ├── product-decisions.md      # Decision log
    ├── output-standards.md       # Quality bar
    └── product-types/
        ├── knowledge-products.md
        ├── template-products.md
        ├── software-products.md
        └── service-products.md

If no product slug is known, offer to create a new product or select from existing.

Reference Lookup Protocol

This skill uses progressive disclosure for product-type guidance:

  1. Read ./references/product-types-index.csv — lightweight index of product families
  2. Match user's product type to family column
  3. Read ONLY the matched product-type guidance from curated files
  4. Never bulk-read all product-type files

Escalation Routes

As the orchestrator, this skill routes to specialists based on user needs:

SignalRoutes ToStage
Idea expansion, concept shapingpaw-ps-discoveryDiscovery
Competitor analysis, market researchpaw-ps-researchResearch
Customer insights, persona buildingpaw-ps-audienceAudience
Product definition, scope, packagingpaw-ps-strategistStrategy
Course, ebook, membership creationpaw-ps-knowledge-executorExecution
Templates, prompt packs, digital kitspaw-ps-template-executorExecution
SaaS, apps, AI toolspaw-ps-software-executorExecution
Productized services, consulting packagespaw-ps-service-executorExecution
Research → brief synthesispaw-ps-research-to-briefSynthesis
Brief → plan synthesispaw-ps-concept-to-product-planSynthesis
Package product artifactspaw-ps-product-package-assemblerPackaging
Readiness reviewpaw-ps-publish-ready-checkQuality

Routing heuristics:

  • Single-skill requests → route directly to specialist
  • Multi-stage work → orchestrate via workflows
  • Ambiguous requests → diagnose stage, then route
  • New product ideas → start with discovery or research

Output Contract

Every coordination deliverable includes:

  • Action type: routing decision, product initialization, stage transition, or progress update
  • Product: which product this applies to
  • Current stage: where the product is in the journey
  • Recommended next action: what the user should do next
  • Specialists involved: which skills were routed to or recommended
  • File saved to: resolved path where the coordination artifact was written

Product Journey Stages

Discovery → Research → Audience → Strategy → Execution → Packaging → Readiness
    │          │          │          │           │           │           │
    ▼          ▼          ▼          ▼           ▼           ▼           ▼
 Discovery   Research   Audience  Strategist   Executor   Assembler   QC
   Agent      Agent      Agent      Agent       Agent     Workflow   Workflow

Stage progression rules:

  • Each stage builds on prior work
  • Quality gates exist before execution
  • User can revisit earlier stages
  • Sidecar memory preserves all context

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Paw Ps Agent Product Builder AI skill do?

Product orchestrator for Prodig Suites that guides product planning, routes work to specialists, and coordinates execution across the product lifecycle. Use when the user is shaping a digital product, deciding next steps, or needs help choosing the right Prodig specialist or workflow. Triggers: 'prodig', 'digital product', 'product idea', 'product planning', 'which product agent should I use', 'SaaS planning', 'course creation', 'template pack', 'productized service'.

Why use Paw Ps Agent Product Builder on TypingMind?

Because you install it once and use it with any model. Paw Ps Agent Product Builder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Paw Ps Agent Product Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/pawbytes/skill-suites/tree/main/src/prodig/paw-ps-agent-product-builder. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Paw Ps Agent Product Builder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Paw Ps Agent Product Builder?

As many as you like. As long as a model supports skills, you can use Paw Ps Agent Product Builder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Paw Ps Agent Product Builder AI skill free?

Yes. It is published on GitHub by pawbytes under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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