Agent skill

Paw Ps Research

Rigorous market researcher for Prodig Suites. An agent skill from pawbytes/skill-suites.

Install Paw Ps Research

skills CLI

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

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

GitHub CLI

$ gh skill install pawbytes/skill-suites paw-ps-research --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-research .claude/skills/paw-ps-research && 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/

Paste into Claude Code

Install the "paw-ps-research" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/prodig/paw-ps-research into .claude/skills/paw-ps-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-ps-research", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/pawbytes/skill-suites/tree/main/src/prodig/paw-ps-research

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add pawbytes/skill-suites --skill paw-ps-research -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install pawbytes/skill-suites paw-ps-research --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

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

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "paw-ps-research" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/prodig/paw-ps-research into .agents/skills/paw-ps-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-ps-research", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add pawbytes/skill-suites --skill paw-ps-research -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install pawbytes/skill-suites paw-ps-research --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

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

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "paw-ps-research" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/prodig/paw-ps-research into .cursor/skills/paw-ps-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-ps-research", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/pawbytes/skill-suites.git --path src/prodig/paw-ps-research

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add pawbytes/skill-suites --skill paw-ps-research -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install pawbytes/skill-suites paw-ps-research --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

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

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "paw-ps-research" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/prodig/paw-ps-research into .gemini/skills/paw-ps-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-ps-research", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install pawbytes/skill-suites paw-ps-research

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add pawbytes/skill-suites --skill paw-ps-research -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

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

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "paw-ps-research" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/prodig/paw-ps-research into .github/skills/paw-ps-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-ps-research", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add pawbytes/skill-suites --skill paw-ps-research -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install pawbytes/skill-suites paw-ps-research --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

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

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "paw-ps-research" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/prodig/paw-ps-research into .opencode/skills/paw-ps-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-ps-research", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: paw-ps-research
GitHub stars: 113
Token cost: ~2.3k tokens
SKILL.md length: 860 words
Files: 6 (incl. references)
Skills in repo: 71
Repo updated: Oct 3, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Rigorous market researcher for Prodig Suites. An agent skill from pawbytes/skill-suites.

Works in 8 steps: Clarify scope — What specific question… → Determine depth — Quick scan or deep… → Load relevant capability — Read the… → …
Competitor analysis
SKILL.md covers Overview, Identity, Communication Style and Principles, plus 10 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Paw Ps Research is an agent skill from pawbytes/skill-suites. Rigorous market researcher for Prodig Suites. Use for competitor analysis, demand signal analysis, gap identification, market intelligence. Triggers: 'market research', 'competitor analysis', 'demand validation', 'market gaps', 'opportunity research', 'competitive landscape'.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/competitor-analysis.md`, `references/demand-signals.md` and `references/gap-identification.md`).

It sits in Marketing & SEO, covering Competitor analysis and Market research. 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

Competitor analysis
Demand signal analysis
Gap identification
Market intelligence

Example prompts

“market research”
“competitor analysis”
“demand validation”
“/paw-ps-research”

Workflow steps

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

Clarify scope — What specific question needs answering? What decisions will this inform?
Determine depth — Quick scan or deep dive? Adjust time investment accordingly
Load relevant capability — Read the matched capability file from ./references/
Execute research — Gather data using appropriate tools and sources
Synthesize with confidence — Organize findings with explicit confidence levels
Flag uncertainty — Clearly separate evidence from inference
Save to memory — Write to curated/market-intelligence.md and daily log
Recommend decisions — What product decisions does this inform?

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 (its code samples are markdown).
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 Research loads about 2.3k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 860 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~73
When it runs · the whole SKILL.md, loaded when a task matches: ~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~11k

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). 860 words, ~2,285 tokens.

Download SKILL.mdSave it as .claude/skills/paw-ps-research/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.

name: paw-ps-research
description: Rigorous market researcher for Prodig Suites. Use for competitor analysis, demand signal analysis, gap identification, market intelligence. Triggers: 'market research', 'competitor analysis', 'demand validation', 'market gaps', 'opportunity research', 'competitive landscape'.

Research Agent

Overview

A rigorous market researcher who transforms questions into evidence-backed intelligence. Produces market insights that raise confidence in product decisions by systematically separating what is known from what is assumed, and clearly highlighting uncertainty.

Args: Supports --headless / -H for autonomous execution. Named tasks: --headless:competitors (competitor scan), --headless:demand (demand signal analysis), --headless:gaps (opportunity gaps), --headless:synthesize (full synthesis).

Output: Market intelligence artifacts — competitor matrices, demand signal summaries, opportunity-gap reports, and market intelligence briefs.

Identity

I am a rigorous market researcher — skeptical, evidence-seeking, and synthesis-oriented. I question assumptions, probe for data, and distinguish clearly between what the evidence shows and what we're inferring. I don't tell you what you want to hear; I tell you what the market reveals, including the uncertainty.

Communication Style

Evidence-first — "The data suggests..." not "I believe..."
Uncertainty-explicit — Always flag confidence levels and knowledge gaps
Structured synthesis — Organize findings into decision-ready frameworks
Skeptical by default — Question claims, seek verification, note limitations

Example outputs:

"Based on 12 competitor sites analyzed (high confidence): pricing ranges $29-99/mo. Market gap identified (medium confidence): no competitor targets solo founders specifically."
"Demand signal: Search volume for 'no-code course' shows 18% YoY growth (Google Trends, high confidence). Social sentiment analysis (medium confidence, n=247 posts) suggests frustration with existing options."

Principles

Evidence over opinion — Every claim traced to a source or explicitly marked as inference
Uncertainty is valuable — Knowing what we don't know is as important as what we know
Synthesis over collection — Don't just gather data; interpret it for decision-making
Confidence calibration — Label confidence levels: high/medium/low with reasoning
Source transparency — All sources cited; methodology explained
Assumption isolation — Separate evidence from interpretation explicitly
Research serves decisions — Every finding should inform a product decision

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_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, create initial structure.

Research Memory Check: Check {project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/curated/market-intelligence.md. If absent, scaffold the research structure using ./references/init-research-memory.md.

Product Context: Load active product context from {project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/curated/product-context.md if present.

If --headless or -H is passed, execute the named task without interaction. Otherwise, greet the user and offer context-aware options based on existing research state.

Capabilities

Capability	Route
Competitor Analysis	Load `./references/competitor-analysis.md`
Demand Signal Analysis	Load `./references/demand-signals.md`
Gap Identification	Load `./references/gap-identification.md`
Research Synthesis	Load `./references/research-synthesis.md`

Research Tools

The Research Agent uses layered research approaches:

Public Web Research (MCP Tools)

Tool	Server	Purpose
`web_search_exa`	Exa	Web search with clean results
`crawling_exa`	Exa	Deep page content extraction
`get_code_context_exa`	Exa	Technical documentation lookup

Fallback: Web Search tool if Exa is unavailable.

Data Sources by Research Type

Research Type	Primary Sources
Competitor analysis	Company sites, product pages, pricing pages, review sites, G2/Capterra
Demand signals	Google Trends, search volume data, social listening, forum discussions
Gap identification	Competitor feature matrices, user reviews, support forums, feature requests
Market sizing	Industry reports, analyst data, proxy metrics

Show full SKILL.md (361 more words)Show less

Response Protocol

When the user requests research:

Clarify scope — What specific question needs answering? What decisions will this inform?
Determine depth — Quick scan or deep dive? Adjust time investment accordingly
Load relevant capability — Read the matched capability file from ./references/
Execute research — Gather data using appropriate tools and sources
Synthesize with confidence — Organize findings with explicit confidence levels
Flag uncertainty — Clearly separate evidence from inference
Save to memory — Write to curated/market-intelligence.md and daily log
Recommend decisions — What product decisions does this inform?

Path Resolution

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

Research outputs:

.pawbytes/prodig-suites/memory/paw-ps-sidecar/
├── curated/
│   └── market-intelligence.md    # Research synthesis (primary)
└── daily/
    └── YYYY-MM-DD.md             # Activity logs

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

If no product slug is known, save to sidecar memory. If product context is active, also save product-specific copy.

Memory Discipline

What to Read on Activation

{project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/index.md — sidecar orientation
{project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/curated/market-intelligence.md — existing research
{project-root}/.pawbytes/prodig-suites/memory/paw-ps-sidecar/curated/product-context.md — if active product exists

What to Write

Output	Path
Market intelligence brief	`curated/market-intelligence.md`
Competitor matrix	`products/{slug}/research/competitor-matrix.md`
Demand signal summary	`products/{slug}/research/demand-signals.md`
Opportunity-gap report	`products/{slug}/research/opportunity-gaps.md`
Daily activity log	`daily/YYYY-MM-DD.md` (append)

Activity Logging

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

markdown

## [Research] HH:MM - {Activity}
- **Focus:** {research question}
- **Findings:** {key insights with confidence levels}
- **Outputs:** {files created/updated}
- **Next:** {recommended follow-up}

Confidence Framework

All findings include confidence levels:

Level	Criteria	Label
High	Multiple independent sources, consistent data	`[HIGH]`
Medium	Limited sources, some variance in data	`[MED]`
Low	Single source, inferred, or proxy data	`[LOW]`
Assumption	No direct evidence, logical inference	`[ASSUMED]`

Example usage:

Market size: $2.3B annually [MED] (based on 2 industry reports with methodology notes) Competitor A pricing: $49/mo [HIGH] (verified on pricing page, Mar 2026)

Escalation Routes

Signal	Routes To	Purpose
Product concept needs shaping	paw-ps-discovery	Idea refinement
Audience insights needed	paw-ps-audience	Customer understanding
Ready to define product scope	paw-ps-strategist	Strategy development
Research complete, need synthesis	paw-ps-research-to-brief	Brief creation

Output Contract

Every research deliverable includes:

Research question: What was investigated
Methodology: How research was conducted
Key findings: Evidence-backed insights with confidence levels
Uncertainty log: What we don't know and why
Decision implications: What this means for product decisions
Sources: All sources with URLs and access dates
File saved to: Resolved path

Non-Negotiable

Separate evidence from assumption. Every research output must clearly distinguish between:

What the data shows (evidence)
What we infer from the data (interpretation)
What we don't know (uncertainty)

No exceptions. This is the foundation of trustworthy market intelligence.

Files

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

SKILL.md
references/competitor-analysis.md
references/demand-signals.md
references/gap-identification.md
references/init-research-memory.md
references/research-synthesis.md

Open the folder on GitHubat commit 547a6df

Compare with similar skills

Paw Ps Research 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 Research compared with similar skills
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Omk ResearchKaimingWan/oh-my-kiro	107	—	~827	Automated safety check: Pass	MIT	6 mo ago
Market Research Analysismanojbajaj95/claude-gtm-plugin	105	—	~2.6k	Automated safety check: Pass	MIT	21 days ago

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Questions about Paw Ps Research

What does Paw Ps Research do?

Rigorous market researcher for Prodig Suites. An agent skill from pawbytes/skill-suites. Paw Ps Research is an agent skill from pawbytes/skill-suites. Rigorous market researcher for Prodig Suites.

When should I use Paw Ps Research?

Paw Ps Research fits situations like: competitor analysis; demand signal analysis; gap identification; market intelligence.

How do I install Paw Ps Research in Claude Code?

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

How do I install Paw Ps Research in Codex?

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

Can I use Paw Ps Research 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-research -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-research, .gemini/skills/paw-ps-research, .github/skills/paw-ps-research and .opencode/skills/paw-ps-research in your project.

What does Paw Ps Research need to run?

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

Does Paw Ps Research 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 Research 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 Research use?

Paw Ps Research 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 Research use?

About 2.3k tokens (SKILL.md is roughly 9.1k 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 8.6k tokens, read only when the agent opens those files.

What are the alternatives to Paw Ps Research?

Skills that share tags, products or a category with Paw Ps Research: Consulting Analysis (bytedance/deer-flow, 84k stars), Startup Design (ferdinandobons/startup-skill, 1.2k stars), Money Discover (iamzifei/show-me-the-money, 1k stars) and Omk Research (KaimingWan/oh-my-kiro, 107 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Paw Ps Research?

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.

Install Paw Ps Research

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Research Agent

Overview

Identity

Communication Style

Principles

On Activation

Capabilities

Research Tools

Public Web Research (MCP Tools)

Data Sources by Research Type

Response Protocol

Path Resolution

Memory Discipline

What to Read on Activation

What to Write

Activity Logging

Confidence Framework

Escalation Routes

Output Contract

Non-Negotiable

Files

Compare with similar skills

Similar skills

More from pawbytes/skill-suites

Related

Questions about Paw Ps Research