A creative planning role for a data-driven blog or article. It decides how findings should be shown through charts, images, videos, audio, maps, interactive demonstrations, or text, and gives those instructions to the person who builds the page.

Use it to plan visuals for each article section, generate selected assets, and create a structured brief for the page builder. In fast mode, it plans charts and static images only.

It connects the type of data with a suitable visual or interactive explanation instead of applying the same media format everywhere. It also keeps the visual choices tied to the actual findings.

designer — Skill for Claude Code by QinghongLin

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 QinghongLin/data2story-skill --skill designer

Clone the repo

git clone --depth 1 https://github.com/QinghongLin/data2story-skill

Made for: Claude Code.

Or install data2story-pro, the plugin that ships this one along with the rest of its 25 skills.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/qinghonglin/data2story-skill/designer/github.svg)](https://agentmods.dev/skills/qinghonglin/data2story-skill/designer)

Your own site

<a href="https://agentmods.dev/skills/qinghonglin/data2story-skill/designer"><img src="https://agentmods.dev/badge/skills/qinghonglin/data2story-skill/designer/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/qinghonglin/data2story-skill/designer"><img src="https://agentmods.dev/badge/skills/qinghonglin/data2story-skill/designer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 8,801 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 warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Excessive Agency · line 133
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00060	$0.08801
Opus 5	$0.00030	$0.04401
Sonnet 5	$0.00012	$0.01760
Haiku 4.5	$0.00006	$0.00880

Measured 10d ago against content hash 246e00de6906, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

designer 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 10d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/openrouter-embeddings/scripts/embed.py, scripts/openrouter-image2video/scripts/generate_video_from_image.py, scripts/openrouter-text2image/scripts/generate_image.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.

skills/data2story-pro/designer/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Designer

Your job is creative visual thinking. For every section of the blog, decide how to make the finding land in the most engaging, memorable way based on the data's actual properties. You do not write HTML — that is the Programmer's job.

Think like a creative director, not a developer. Your output is a precise visual brief that tells the Programmer exactly what to build. Do not satisfy a fixed media checklist. Let the data, story, and editorial rhythm determine whether each section needs a chart, image, video, audio, map, interactive, stat callout, instance, or text-only treatment.

Fast profile. When run_config.json says run_profile: "fast", design charts + static images only — no text2video / image2video / text2music generation, no animated hero (a static cover image is fine), and no cinematic scroll (those roles are skipped in fast). Charts plus a few license-clean / fetched (or a single generated) static images carry the page. The full five-channel multimedia brief below is the premium profile.

Setup

PROJECT_DIR = first argument
Resolve SKILL_DIR = the directory containing this SKILL.md (.../skills/data2story-pro/designer). Replace SKILL_DIR placeholders with the resolved, quoted path before running Bash. Do not hard-code machine-local paths.
Read PROJECT_DIR/editor.md, PROJECT_DIR/editor.json, PROJECT_DIR/analyst.json, and PROJECT_DIR/scout.json (if present) before doing anything
Read the shared design system in ../../frontend-design-pro/ (SKILL.md + references/) and choose a theme + component vocabulary for this story
Assets go in PROJECT_DIR/assets/
Output: PROJECT_DIR/designer.json

How to read the input files

editor.md: the prose document with section structure. Each section has an edt_xx ID, lists its evidence (ana_xx) and context (det_xx), and contains the verbatim text.
editor.json: machine-readable sections. Each edt_xx has findings, chart_placeholder (which ana_xx drives the chart), a typed media_placeholder, and editorial_notes.
analyst.json: items keyed by ana_xx. Each has content, calculation, and crucially data_table (chart-ready data) — review it to understand what data is available for each chart.

Read the full file on GitHub · 149 lines

Files

What ships with it

23 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

10d ago First seen · 149 lines · 60 tokens per session scan A 246e00de6906

Subscribe to this mod's changes

designer is a skill published in the GitHub repository QinghongLin/data2story-skill (155 stars, last pushed 2mo ago), licensed MIT. It adds 60 tokens to every session and 8,801 once invoked, about $0.0003 per session on Opus 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.

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