faostat-viz

faostat-viz is a skill for Claude Code from berba-q/faostat-skills. It costs 140 tokens per session (2,104 once invoked), scanned A, original, MIT.

A guide for turning FAOSTAT agricultural statistics into interactive charts in a standalone HTML file. FAOSTAT is the Food and Agriculture Organization's database of food and farming data.

In plain words
What is it for?
Creating line, bar, stacked-bar, and scatter charts from FAOSTAT data, with responsive layout, accessibility details, and data attribution.
Why use it?
It helps choose a suitable chart for trends, category comparisons, composition, or relationships instead of presenting raw statistics alone.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the faostat-skills plugin — 14 skills, 14 commands shipped together

Good fit Creating line, bar, stacked-bar, and scatter charts from FAOSTAT data, with responsive layout, accessibility details, and data attribution.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/berba-q/faostat-skills/viz
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 berba-q/faostat-skills --skill viz
Clone the repo
git clone --depth 1 https://github.com/berba-q/faostat-skills

Made for: Claude Code.

Or install faostat-skills, the plugin that ships this one along with the rest of its 14 skills, 14 commands.

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 faostat-viz

README.md
[![agentmods](https://agentmods.dev/badge/skills/berba-q/faostat-skills/viz/github.svg)](https://agentmods.dev/skills/berba-q/faostat-skills/viz)
Your own site
<a href="https://agentmods.dev/skills/berba-q/faostat-skills/viz"><img src="https://agentmods.dev/badge/skills/berba-q/faostat-skills/viz/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 faostat-viz

Your own site · 80×15
<a href="https://agentmods.dev/skills/berba-q/faostat-skills/viz"><img src="https://agentmods.dev/badge/skills/berba-q/faostat-skills/viz.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 140 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,104 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.
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 $0.00140 $0.02104
Opus 5 $0.00070 $0.01052
Sonnet 5 $0.00028 $0.00421
Haiku 4.5 $0.00014 $0.00210

Measured 11d ago against content hash b0df21453f53, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

faostat-viz 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 11d ago.

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/viz/SKILL.md · 170 lines

How it starts

The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.

FAOSTAT Data Visualizer

Generate interactive, standalone HTML charts from FAOSTAT data. Charts use Chart.js via CDN and are designed to be self-contained, responsive, accessible, and properly attributed.

Prerequisites

Before starting, verify that the FAOSTAT MCP tools are available: faostat_search_codes, faostat_get_data. If they are not available and the user has not provided data in the conversation context, inform the user they need the FAOSTAT MCP server configured and stop.

If data is already available in the conversation context (e.g., from a previous query or another skill), skip directly to chart generation.

Chart Type Selection

Choose the chart type based on the data relationship. If the user does not specify a chart type, select the most appropriate one:

Data Relationship Chart Type When to Use
Values over time Line chart Trends, time series, historical data
Values across categories Bar chart Comparing countries, commodities, or regions
Composition breakdown Stacked bar chart Shares of a total (e.g., emissions by source, trade by partner)
Two-variable relationship Scatter plot Correlations (e.g., fertilizer use vs. emissions)

Do NOT use pie charts. They are difficult to read with more than 3-4 categories and do not convey FAOSTAT data well.

Workflow

Step 1: Determine data source

Check if usable data already exists in the conversation context:

  • If YES: extract the relevant data points (values, labels, years, units) and proceed to Step 4.
  • If NO: proceed to Step 2 to query FAOSTAT.

Step 2: Query data (if needed)

  1. Ask the user what they want to visualize if not clear from context:

    • What metric? (production, yield, trade volume, emissions, etc.)
    • Which entities? (countries, commodities, regions)
    • What time range?
  2. Resolve all codes using faostat_search_codes:

    • Resolve area codes: faostat_search_codes(domain_code='<domain>', dimension_id='area', query='<name>')
    • Resolve item codes: faostat_search_codes(domain_code='<domain>', dimension_id='item', query='<name>')
    • Handle requires_confirmation for every search -- present options and wait for user choice.

Read the full file on GitHub · 170 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. 11d ago First seen · 170 lines · 140 tokens per session scan A b0df21453f53

Subscribe to this mod's changes

faostat-viz is a skill published in the GitHub repository berba-q/faostat-skills (7 stars, last pushed 4mo ago), licensed MIT. It adds 140 tokens to every session and 2,104 once invoked, about $0.0007 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 2026-08-31.

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