ip-hand-drawn-infographic-planner

ip-hand-drawn-infographic-planner is a skill for Codex from zkbys/whiteboard. It costs 94 tokens per session (953 once invoked), scanned A, original, MIT.

A planning skill that turns a short-video script and its visual beats into a compact hand-drawn infographic plan. The plan describes boards, diagrams, and image prompts for later creation.

In plain words
What is it for?
Use it to prepare infographic plans, board specification files, and image prompts for business, intellectual-property, or AI explainer videos.
Why use it?
It separates visual planning from image and video production, so the message can be organized before assets are generated. It also prevents the board from simply copying every spoken sentence.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it to prepare infographic plans, board specification files, and image prompts for business, intellectual-property, or AI explainer videos.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zkbys/whiteboard/ip-hand-drawn-infographic-planner
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zkbys/whiteboard --skill ip-hand-drawn-infographic-planner
Clone the repo
git clone --depth 1 https://github.com/zkbys/whiteboard

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ip-hand-drawn-infographic-planner

README.md
[![agentmods](https://agentmods.dev/badge/skills/zkbys/whiteboard/ip-hand-drawn-infographic-planner/github.svg)](https://agentmods.dev/skills/zkbys/whiteboard/ip-hand-drawn-infographic-planner)
Your own site
<a href="https://agentmods.dev/skills/zkbys/whiteboard/ip-hand-drawn-infographic-planner"><img src="https://agentmods.dev/badge/skills/zkbys/whiteboard/ip-hand-drawn-infographic-planner/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ip-hand-drawn-infographic-planner

Your own site · 80×15
<a href="https://agentmods.dev/skills/zkbys/whiteboard/ip-hand-drawn-infographic-planner"><img src="https://agentmods.dev/badge/skills/zkbys/whiteboard/ip-hand-drawn-infographic-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 953 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00094 $0.00953
Opus 5.5 $0.00038 $0.00381
Sonnet 5.5 $0.00019 $0.00191
Haiku 4.5 $0.00009 $0.00095

Measured 1mo ago against content hash 01048a5f1887, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ip-hand-drawn-infographic-planner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate_infographic_plan.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

ip-hand-drawn-infographic-planner/SKILL.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

IP Hand-Drawn Infographic Planner

Overview

Turn polished short-video voiceover and visual beats into a compact hand-drawn infographic plan. The output prepares structured inputs for hand-drawn-infographic-creator and the later video board control layer.

Non-Goals

  • Do not generate PNGs, videos, audio, subtitles, or HyperFrames projects.
  • Do not replace hand-drawn-infographic-creator; only prepare its prompt-level inputs.
  • Do not write board_manifest.json, motion_plan.json, bbox, camera, cursor, or annotation coordinates.
  • Do not copy the voiceover sentence by sentence onto the board.

Required Inputs

Prefer a project package with:

script/
├── polished_voiceover.md
├── voiceover_segments.json
└── visual_beats.json

If only prose voiceover is available, first segment it into stable segment ids and visual beats before writing infographic outputs.

Workflow

  1. Read references/schema.md before writing outputs.
  2. Read references/business-cognition-diagram-patterns.md before deciding board count and diagram type.
  3. Read references/hand-drawn-prompt-bridge.md before writing image prompts.
  4. Extract the one core thesis and the few visual beats that actually need a board.
  5. Decide board count:
    • Use one board for one thesis, one contrast, or up to 5 key objects.
    • Use two boards when the voiceover has two separate jobs, usually problem framing plus method/checklist.
    • Use three boards only when the script is longer than the normal 30-60 second package or has clearly separate concepts.
  6. For each board, keep contentDensity as simple, set maxKeyObjects to 3-5, and give every key object a stable semantic id.
  7. Write:
infographic/
├── infographic_plan.json
├── board_specs/
│   └── board-01.board_spec.json
└── image_prompts/
    └── board-01.prompt.md
  1. Run the validator:
python3 ip-hand-drawn-infographic-planner/scripts/validate_infographic_plan.py <project-output>

Planning Rules

Read the full file on GitHub · 81 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 81 lines · 94 tokens per session scan A 01048a5f1887

Subscribe to this mod's changes

ip-hand-drawn-infographic-planner is a skill published in the GitHub repository zkbys/whiteboard (58 stars, last pushed 3mo ago), licensed MIT. It adds 94 tokens to every session and 953 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Optimize the meaningful UI available immediately from a Next.js route on an initial load (hard navigation) or named client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route and entry point at a time; the shipped test then guards…

vercel/next.js · 123 tokens