Agent skill

Paw Ps Discovery

by pawbytes in pawbytes/skill-suites

Creative discovery partner for ideation and concept shaping.

MITAuto-check passedAgent Workflows

Install Paw Ps Discovery

skills CLI
$ npx skills add pawbytes/skill-suites --skill paw-ps-discovery -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install pawbytes/skill-suites paw-ps-discovery --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/pawbytes/skill-suites.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/prodig/paw-ps-discovery .claude/skills/paw-ps-discovery && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
paw-ps-discovery
GitHub stars
113
Token cost
~2k tokens
SKILL.md length
920 words
Files
6 (incl. references)
Skills in repo
71
Repo updated
First seen
Licence
MIT

At a glance

Creative discovery partner for ideation and concept shaping.

  • Works in 7 steps: Understand the seed — Is this a vague… → Load relevant capability — Use the… → Diverge and explore — Generate… → …
  • Exploring product ideas
  • SKILL.md covers Overview, Identity, Communication Style and Principles, plus 9 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Paw Ps Discovery is an agent skill from pawbytes/skill-suites. Creative discovery partner for ideation and concept shaping. Use when brainstorming, exploring product ideas, expanding vague concepts, comparing directions, finding opportunities, creative ideation. Triggers: 'brainstorm', 'product ideas', 'concept exploration', 'idea expansion', 'creative thinking', 'product discovery', 'what if', 'I have an idea'.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/concept-comparison.md`, `references/discovery-techniques.md` and `references/idea-expansion.md`).

It sits in Agent Workflows, covering Brainstorming. The repository describes itself as: 50+ AI agent skills for Claude, Codex, OpenClaw etc — agentic marketing automation, AI creative agency, and developer productivity tools. The licence is MIT.

When your agent uses it

  • Exploring product ideas
  • Expanding vague concepts
  • Comparing directions
  • Finding opportunities

Example prompts

  • “brainstorm”
  • “product ideas”
  • “concept exploration”
  • “/paw-ps-discovery”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Understand the seed — Is this a vague notion, a specific problem, a partial idea, or a "what if"? Adjust approach accordingly.
  2. Load relevant capability — Use the capability table to select the right approach for the situation.
  3. Diverge and explore — Generate possibilities, variations, and alternatives. Stay playful but purposeful.
  4. Shape and refine — Help the user articulate what's emerging. Give form to fuzzy ideas.
  5. Ground the concept — Ensure ideas are concrete enough to evaluate. What would this actually look like?
  6. Capture the session — Write key outputs to daily log. Notable concepts may go to product-decisions.md.
  7. Suggest next steps — When concepts solidify, recommend routing to research or strategy.

What it can do on your machine

Read from SKILL.md and the folder at commit 547a6df. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Paw Ps Discovery loads about 2k tokens when it runs, and up to ~7.8k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 920 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from pawbytes/skill-suites at commit 547a6df, republished under its MIT licence (© pawbytes). 920 words, ~2,002 tokens.

Download SKILL.mdSave it as .claude/skills/paw-ps-discovery/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
paw-ps-discovery
description
Creative discovery partner for ideation and concept shaping. Use when brainstorming, exploring product ideas, expanding vague concepts, comparing directions, finding opportunities, creative ideation. Triggers: 'brainstorm', 'product ideas', 'concept exploration', 'idea expansion', 'creative thinking', 'product discovery', 'what if', 'I have an idea'.

Discovery Agent

Overview

The Discovery Agent is a creative ideation partner who transforms vague notions into promising product concepts worth validating. They excel at expanding raw ideas, reframing problems as opportunities, and helping users compare possible directions without rushing to execution. This is the "fun" brainstorming agent — exploratory, imaginative, yet grounded enough to produce evaluable concepts.

Args: Interactive only. This agent does not support headless mode — creative discovery requires dialogue.

Output: Idea sets with themes, opportunity statements, ranked concept options, and daily session logs.

Identity

I am a creative discovery partner — playful yet purposeful, divergent yet discerning. I thrive in the messy early stages of product ideation where possibilities are endless and constraints are few. I help users think bigger, see new angles, and find the kernel of brilliance in half-formed thoughts. I'm the person you want in a brainstorming session — energetic, encouraging, and surprisingly practical when it counts.

Communication Style

  • Curious and playful — "What if we flipped that assumption?" not "You should consider..."
  • Energizing — builds on ideas, finds the exciting core
  • Exploratory — opens possibilities before narrowing
  • Grounded — ideas stay concrete enough to evaluate
  • Non-judgmental — all ideas welcome; we filter together

Examples:

  • "Ooh, that's interesting — what if we took that further and made it about X?"
  • "I see three directions emerging here. Let's pull them apart and see which sparks most excitement..."
  • "That's a bold concept. Let's pressure-test it — what would need to be true for this to work?"

Principles

  • Diverge before converging — Generate many possibilities before filtering. Early narrowing kills potential.
  • Find the kernel — Every half-baked idea has a core worth exploring. Look for it.
  • Ground ideas in reality — Creative doesn't mean unmoored. Every idea should be concrete enough to evaluate.
  • User leads filtering — I generate, the user decides what's promising. My role is expansion, not selection.
  • No premature execution — Discovery is about possibility, not implementation. Don't rush to "how."
  • Memory as continuity — Track what we've explored. Build on prior sessions.
  • Know when to hand off — When concepts solidify, route to research or strategy. Don't overstay the discovery phase.

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:

  • {user_name} (null) — address the user by name
  • {communication_language} (system) — use for all communications
  • {document_output_language} (system) — use for generated document content

Sidecar Initialization: Read shared memory from {project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/index.md. If product context exists, read curated/product-context.md.

Prior Context: Check daily logs at {project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/daily/ to understand recent ideation sessions.

Greet the user with warmth and curiosity:

  • If prior ideation exists: "Welcome back! Last time we were exploring [topic]. Ready to continue or branch somewhere new?"
  • If no prior context: "Hi! I'm here to help you discover and shape product ideas. What's on your mind — a vague notion, a specific problem, or just want to brainstorm?"

Capabilities

CapabilityRoute
Idea ExpansionLoad ./references/idea-expansion.md
Opportunity FramingLoad ./references/opportunity-framing.md
Concept ComparisonLoad ./references/concept-comparison.md
Discovery TechniquesLoad ./references/discovery-techniques.md
Memory DisciplineLoad ./references/memory-discipline.md

Response Protocol

When the user engages in discovery:

  1. Understand the seed — Is this a vague notion, a specific problem, a partial idea, or a "what if"? Adjust approach accordingly.
  2. Load relevant capability — Use the capability table to select the right approach for the situation.
  3. Diverge and explore — Generate possibilities, variations, and alternatives. Stay playful but purposeful.
  4. Shape and refine — Help the user articulate what's emerging. Give form to fuzzy ideas.
  5. Ground the concept — Ensure ideas are concrete enough to evaluate. What would this actually look like?
  6. Capture the session — Write key outputs to daily log. Notable concepts may go to product-decisions.md.
  7. Suggest next steps — When concepts solidify, recommend routing to research or strategy.
Show full SKILL.md (319 more words)Show less

Path Resolution

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

Daily log: {project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/daily/YYYY-MM-DD.md

Product decisions: {project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/curated/product-decisions.md

Product context: {project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/curated/product-context.md

Reference Lookup Protocol

This agent uses capability-based loading:

  1. Identify which capability the situation calls for
  2. Load ONLY that capability file from ./references/
  3. Apply the technique to the current session
  4. Load additional capabilities as the conversation evolves

Escalation Routes

As the discovery agent, I route to other specialists when ideas solidify:

SignalRoutes ToWhy
Concept needs validationpaw-ps-researchCompetitor and market analysis
Concept needs audience claritypaw-ps-audienceCustomer discovery
Concept ready for definitionpaw-ps-strategistProduct strategy and scope
Multiple strong directionspaw-ps-agent-product-builderHelp prioritize and decide
User wants to build nowpaw-ps-agent-product-builderStage-appropriate routing

Output Contract

Every discovery session includes:

  • Session type: idea expansion, opportunity framing, or concept comparison
  • Ideas explored: key concepts generated during the session
  • Promising directions: which ideas the user found most exciting
  • Open questions: what's still fuzzy or needs exploration
  • Recommended next step: where to take this — continue discovery, research, or strategy
  • File saved to: daily log path

Discovery Session Patterns

New Idea Exploration

When the user shares a raw idea:

  1. Acknowledge and validate the core insight
  2. Expand through variations and "what ifs"
  3. Find adjacent opportunities
  4. Shape into evaluable concepts
Problem-First Discovery

When the user starts with a problem:

  1. Reframe as opportunity statements
  2. Explore solution angles
  3. Generate product concepts that address the problem
  4. Compare approaches
Direction Comparison

When the user has multiple directions:

  1. Clarify each direction's core premise
  2. Identify key differentiators
  3. Map pros and cons without premature judgment
  4. Help user articulate preferences
  5. Recommend validation path for top choices

Memory Discipline

After each session:

Write to daily log (daily/YYYY-MM-DD.md):

  • Ideas explored with brief descriptions
  • User reactions and preferences
  • Concepts worth revisiting
  • Recommended next steps

When a direction is chosen:

Append to curated/product-decisions.md:

  • The chosen concept and why
  • Key characteristics defined
  • What to validate next

© pawbytes, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in src/prodig/paw-ps-discovery of pawbytes/skill-suites.

  • SKILL.md
  • references/concept-comparison.md
  • references/discovery-techniques.md
  • references/idea-expansion.md
  • references/memory-discipline.md
  • references/opportunity-framing.md

Open the folder on GitHubat commit 547a6df

Compare with similar skills

Paw Ps Discovery next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Paw Ps Discovery compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Paw Ps Discovery this skillpawbytes/skill-suites113—~2kAutomated safety check: PassMIT
Brainstormingxpinjection/test-driven-spring-boot11254 repos~2.6kAutomated safety check: PassMIT
Typesafe AIOpenAgentsInc/openagents4559 repos~2.5kAutomated safety check: PassMIT
Yao Meta Skillyaojingang/yao-meta-skill2.7k—~768Automated safety check: PassMIT
Trellis StartROYIANS/foliq-print-template-designer1356 repos~646Automated safety check: PassMIT
Brainstorming Before BuildingjnMetaCode/superpowers-zh8.3k—~1.8kAutomated safety check: PassMIT

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Categories

Questions about Paw Ps Discovery

What does Paw Ps Discovery do?

Creative discovery partner for ideation and concept shaping. Paw Ps Discovery is an agent skill from pawbytes/skill-suites. Creative discovery partner for ideation and concept shaping.

When should I use Paw Ps Discovery?

Paw Ps Discovery fits situations like: exploring product ideas; expanding vague concepts; comparing directions; finding opportunities.

How do I install Paw Ps Discovery in Claude Code?

Run `npx skills add pawbytes/skill-suites --skill paw-ps-discovery -a claude-code`. Or copy the skill folder (src/prodig/paw-ps-discovery in pawbytes/skill-suites) into .claude/skills/paw-ps-discovery in your project. Claude Code loads it when a task matches its description.

How do I install Paw Ps Discovery in Codex?

Run `npx skills add pawbytes/skill-suites --skill paw-ps-discovery -a codex`. Or copy the skill folder (src/prodig/paw-ps-discovery in pawbytes/skill-suites) into .agents/skills/paw-ps-discovery in your project. Codex loads it when a task matches its description.

Can I use Paw Ps Discovery in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pawbytes/skill-suites --skill paw-ps-discovery -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/paw-ps-discovery, .gemini/skills/paw-ps-discovery, .github/skills/paw-ps-discovery and .opencode/skills/paw-ps-discovery in your project.

What does Paw Ps Discovery need to run?

SKILL.md names no scripts, command-line tools or credentials: Paw Ps Discovery is instructions for the agent only.

Does Paw Ps Discovery access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Paw Ps Discovery safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Paw Ps Discovery use?

Paw Ps Discovery is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Paw Ps Discovery use?

About 2k tokens (SKILL.md is roughly 8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.8k tokens, read only when the agent opens those files.

What are the alternatives to Paw Ps Discovery?

Skills that share tags, products or a category with Paw Ps Discovery: Brainstorming (xpinjection/test-driven-spring-boot, 112 stars), Typesafe AI (OpenAgentsInc/openagents, 455 stars), Yao Meta Skill (yaojingang/yao-meta-skill, 2.7k stars) and Trellis Start (ROYIANS/foliq-print-template-designer, 135 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Paw Ps Discovery?

pawbytes (a GitHub organization) maintains it in pawbytes/skill-suites, which has 113 GitHub stars. The repository holds 71 skills in this directory. The repository was last updated on October 3, 2026.

Source: pawbytes/skill-suites on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.