Planning With Files
jarrodwatts/claude-code-config
Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage.
End-to-end Product Innovation R&D workflow — inspiration gathering, research, and professional report generation.
$ npx skills add LeoYeAI/openclaw-master-skills --skill product-rnd -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills product-rnd --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/product-rnd .claude/skills/product-rnd && rm -rf skills-srcUse ~/.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/
Install the "product-rnd" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/product-rnd into .claude/skills/product-rnd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-rnd", 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 install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/product-rndType 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.
$ npx skills add LeoYeAI/openclaw-master-skills --skill product-rnd -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills product-rnd --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/product-rnd .agents/skills/product-rnd && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "product-rnd" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/product-rnd into .agents/skills/product-rnd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-rnd", 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.
$ npx skills add LeoYeAI/openclaw-master-skills --skill product-rnd -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills product-rnd --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/product-rnd .cursor/skills/product-rnd && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "product-rnd" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/product-rnd into .cursor/skills/product-rnd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-rnd", 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 https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/product-rnd--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LeoYeAI/openclaw-master-skills --skill product-rnd -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills product-rnd --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/product-rnd .gemini/skills/product-rnd && rm -rf skills-srcUse ~/.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/
Install the "product-rnd" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/product-rnd into .gemini/skills/product-rnd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-rnd", 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.
$ gh skill install LeoYeAI/openclaw-master-skills product-rndInstalls 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).
$ npx skills add LeoYeAI/openclaw-master-skills --skill product-rnd -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/product-rnd .github/skills/product-rnd && rm -rf skills-srcUse ~/.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/
Install the "product-rnd" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/product-rnd into .github/skills/product-rnd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-rnd", 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.
$ npx skills add LeoYeAI/openclaw-master-skills --skill product-rnd -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills product-rnd --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/product-rnd .opencode/skills/product-rnd && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "product-rnd" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/product-rnd into .opencode/skills/product-rnd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-rnd", 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.
product-rndEnd-to-end Product Innovation R&D workflow — inspiration gathering, research, and professional report generation.
Product Rnd is an agent skill from LeoYeAI/openclaw-master-skills. End-to-end Product Innovation R&D workflow — inspiration gathering, research, and professional report generation. Use whenever the user wants to create a product innovation or R&D report, develop a new product concept, conduct NPD research, or generate a structured output for a product or investor audience. Also triggers on "product innovation", "new product development", "product concept", "packaging design brief", or any request to generate a report around a product idea.
Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `_meta.json`).
It sits in AI & LLM Engineering, covering Structured output and tool calling. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
6 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Product Rnd loads about 5k tokens when it runs. Until then it costs about 123 tokens; SKILL.md has 2,444 words of instructions outside code blocks.
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.
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.
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 2,444 words, ~4,963 tokens.
.claude/skills/product-rnd/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.You are a strategic product innovation analyst on the atypica.AI business research intelligence team, specializing in professional product innovation analysis reports for senior decision-makers. You possess deep expertise in business strategy, market analysis, and innovation management, capable of transforming product concepts into compelling business cases and strategic recommendations. Your task is to create professional, serious, visually appealing, logically clear, highly persuasive, and professional HTML innovation reports based on the research gathered above and the initial product inspiration, to report to your superiors and convince them to adopt your proposals. This Skills guides you to do so.
Firstly, based on the product, pick a detailed report style descriptions. Cannot provide style names only, must include specific design instructions: 1) Design Philosophy Description - detailed explanation of overall aesthetic philosophy and design direction (may reference Kenya Hara minimalist aesthetics, Tadao Ando geometric lines, MUJI style, Spotify vitality, Apple design, McKinsey professional style, Bloomberg financial style, Chinese ancient book binding, Japanese wa-style design, etc., but not limited to these - should use imagination to choose professional styles and describe specific characteristics with emotional expression in detail), 2) Visual Design Standards - clearly specify color combination schemes, typography requirements, layout methods with concrete standards, must include emotional visual descriptions and atmosphere creation, 3) Content Presentation Methods - detailed description of content display style requirements, visual element style descriptions, information hierarchy handling methods.
【Core Design Philosophy: The Less AI, the More AI】 Present the most intelligent insights in the most powerful human way. We study people, simulate people, and serve the understanding of people. So the report's visual language should use sophisticated professional techniques (editorial design, architectural photography aesthetics) not cheap tech clichés (neon gradients, 3D renders, gaudy effects). Key Principles:
【Professional Standards】
【Content Generation Principles】
【Product Innovation Specific Design Requirements】
【Report Characteristics】
【Visual Content Enhancement】
【Image Generation】 Dependency: Requires any image generation capability — an installed image gen skill, a model with image generation access, or any available image API. Any tool that can generate images from a prompt will work; there is no required specific model or API. If no image generation capability is found in the environment, the report will lack visual product presentation — recommend the user install an image generation skill before proceeding.
Timing: Generate images ONLY after completing section 8 (Packaging Design)
Content Requirements:
Image Prompt Requirements:
Technical Requirements:
max-w-full or inline style【Technical Implementation】
Innovation Product Solution (Highest information hierarchy, immediately making readers understand the importance of this innovation case and catching their attention, making readers want to continue reading)
Innovation Source
Product Attributes
| Attribute | Content |
|---|---|
| Product Name | |
| Formula/Recipe | |
| Shape/Form | |
| Texture | |
| Sweetness Level | |
| Size/Dimensions | |
| Packaging Type | |
| Visual Style | |
| Opening Method | |
| Shelf Life & Storage |
Benefit (Product Benefits)
RTB (Reason to Believe)
Insight (Market & Consumer Insights)
Market Opportunity Analysis: Competitive Environment Analysis (Essential, can be based on your knowledge if not provided)
Packaging Design (Based on POP/PACE/PULL Principles)
Innovation Solution Uniqueness Verification
Marketing and Promotion Strategy (Essential, please logically design detailed marketing promotion strategies based on the above information)
Before research, gather real-world signals to ground and sharpen the product direction. Use a cross-field search strategy — for a chocolate product, search trending desserts, international recipes, and wellness snacks rather than just the product category itself. This widens the creative spectrum.
If a cron/scheduler harness is available in your environment, offer to set up a recurring daily job that searches for trending signals in the user's product category and saves them to {base_dir}/{project}/signals/YYYYMMDD-HHMM.md. Capture at most 5 high-engagement results per run (quality over quantity), record specific content details and engagement metrics, and propose one R&D inspiration per signal.
If no cron harness is available, perform the same search once manually before starting research and save it as a signals file. If signals already exist in the project's signals directory, review the most recent file and use the strongest signal as the research anchor.
Follow this sequence strictly:
Inspiration Gathering — see the Inspiration Gathering (Phase 0) section above. Set up a daily cron job if a scheduler harness is available, otherwise perform a one-time cross-field signal search. Review any existing signals and select the strongest as a research anchor before proceeding.
Research & Note-Taking
{base_dir}/{Project-Name}/research_note.mdCreate HTML Structure
{base_dir}/{Project-Name}/report.html<!DOCTYPE html>, <html>, <head> with meta tags, Tailwind CSS link, custom styles, <body> opening tagWrite Report Sections Incrementally
report.html.</body></html> tagsGenerate Product & Packaging Images
{base_dir}/{Project-Name}/product-image-1.png, product-image-2.png, product-image-3.pngUpdate HTML with Image References
{base_dir}/{Project-Name}/report.htmlDeliver
html-to-pdf skill is installed, convert the report to PDF for easier reading and sharing:
python skills/html-to-pdf/scripts/html_to_pdf.py {base_dir}/{Project-Name}/report.html {base_dir}/{Project-Name}/report.pdf
Then share the PDF path with the user. If the skill is not installed, share the HTML path instead.© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/product-rnd of LeoYeAI/openclaw-master-skills.
Open the folder on GitHubat commit e5199b5
Product Rnd 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Product Rnd this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~5k | Automated safety check: Pass | MIT | |
| Planning With Filesjarrodwatts/claude-code-config | 1.1k | 5 repos | ~967 | Automated safety check: Pass | None | |
| Tool Use Data Synthesissunny-glow/Auto-BenchMax | 1.3k | — | ~3.3k | Automated safety check: Pass | None | |
| Agent Harness ConstructionKartikLabhshetwar/mind-mentor | 148 | 6 repos | ~500 | Automated safety check: Pass | Apache-2.0 | |
| Prompt Engineering Patternswshobson/agents | 40k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Model Benchmarkstheopenco/llmgateway | 1.7k | — | ~1.1k | Automated safety check: Notes | Custom licence |
jarrodwatts/claude-code-config
Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage.
sunny-glow/Auto-BenchMax
Synthesize training data for ANY tool-use / agentic benchmark, in ANY repo.
KartikLabhshetwar/mind-mentor
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
wshobson/agents
Reference for designing and tuning production LLM prompts: few-shot examples, chain-of-thought, structured outputs, templates and system prompts.
theopenco/llmgateway
Run and report repository model or provider-mapping benchmarks.
mastra-ai/mastra
Universal quality bar and final audit rubric for any agent system prompt.
LeoYeAI/openclaw-master-skills
Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.
LeoYeAI/openclaw-master-skills
Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.
LeoYeAI/openclaw-master-skills
Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.
LeoYeAI/openclaw-master-skills
Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.
LeoYeAI/openclaw-master-skills
Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.
LeoYeAI/openclaw-master-skills
Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.
Categories
End-to-end Product Innovation R&D workflow — inspiration gathering, research, and professional report generation. Product Rnd is an agent skill from LeoYeAI/openclaw-master-skills. End-to-end Product Innovation R&D workflow — inspiration gathering, research, and professional report generation.
Product Rnd fits situations like: the user wants to create a product innovation; develop a new product concept; conduct NPD research; generate a structured output for a product.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill product-rnd -a claude-code`. Or copy the skill folder (skills/product-rnd in LeoYeAI/openclaw-master-skills) into .claude/skills/product-rnd in your project. Claude Code loads it when a task matches its description.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill product-rnd -a codex`. Or copy the skill folder (skills/product-rnd in LeoYeAI/openclaw-master-skills) into .agents/skills/product-rnd in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill product-rnd -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/product-rnd, .gemini/skills/product-rnd, .github/skills/product-rnd and .opencode/skills/product-rnd in your project.
Going by SKILL.md and its folder, Product Rnd needs the command-line tools its instructions call (python).
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.
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.
Product Rnd is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 5k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Product Rnd: Planning With Files (jarrodwatts/claude-code-config, 1.1k stars), Tool Use Data Synthesis (sunny-glow/Auto-BenchMax, 1.3k stars), Agent Harness Construction (KartikLabhshetwar/mind-mentor, 148 stars) and Prompt Engineering Patterns (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.