What is faostat-scientific-paper?

An academic research paper built from FAOSTAT data, the United Nations food and agriculture statistics database. It uses the IMRaD structure—Introduction, Methods, Results and Discussion—and includes supporting data and references.

Use it to write a research paper about food, agriculture or related trends, with figures, tables, statistical analysis and reproducible source data.

It turns agricultural statistics into a documented manuscript that researchers and reviewers can examine.

faostat-scientific-paper — Skill for Claude Code by berba-q

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 scientific-paper

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/berba-q/faostat-skills/scientific-paper/github.svg)](https://agentmods.dev/skills/berba-q/faostat-skills/scientific-paper)

Your own site

<a href="https://agentmods.dev/skills/berba-q/faostat-skills/scientific-paper"><img src="https://agentmods.dev/badge/skills/berba-q/faostat-skills/scientific-paper/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/berba-q/faostat-skills/scientific-paper"><img src="https://agentmods.dev/badge/skills/berba-q/faostat-skills/scientific-paper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 218 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,819 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.

Model	Per session	Once invoked
Fable 5.1	$0.00218	$0.04819
Opus 5.5	$0.00087	$0.01928
Sonnet 5.5	$0.00044	$0.00964
Haiku 4.5	$0.00022	$0.00482

Measured 2mo ago against content hash 1c4da3ff8aab, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

faostat-scientific-paper 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 2mo 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/scientific-paper/SKILL.md · 246 lines

How it starts

The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.

FAOSTAT Scientific Paper

Build a peer-reviewable research paper from FAOSTAT data. Audience is researchers, reviewers and methodologists — not policymakers, not general readers. Length target 3,000–8,000 words, 6–12 numbered figures/tables, 15–40 references. Deliverable bundle: .docx manuscript + .xlsx data appendix + .bib BibTeX file.

Prerequisites

Before starting, confirm FAOSTAT MCP tools are available: faostat_get_data, faostat_search_codes, faostat_list_groups, faostat_list_domains, faostat_get_rankings, faostat_get_metadata. If not, stop and tell the user the skill requires the FAOSTAT MCP server.

Python packages needed for output: python-docx, openpyxl, pandas, scipy (for scipy.stats.kendalltau and Mann–Kendall test — install pymannkendall if available, otherwise implement from scipy.stats). Install with --break-system-packages in the sandbox.

Invariants

Cross-skill invariants (all six — violations are skill bugs):

FILTER vs DISPLAY codes. faostat_get_data takes FILTER codes (e.g., 2510 Production). faostat_get_rankings takes DISPLAY codes (e.g., 5510). Never invert.
Year syntax. Comma-separated lists only ('2010,2011,...,2023'). Colon ranges return empty in practice.
Element filter required on every faostat_get_data call.
TCL for national trade aggregates, TM only for partner breakdowns. Never sum TM rows to reconstruct national totals.
China composite default (Apr 2026 user preference). Country-level numbers and rankings default to composite China (area 351). China, mainland (41) is available as an opt-in — do not substitute 41 unless the user explicitly asks. Flag the choice in the Methods section with the FAOSTAT-default-41 caveat. Map carve-out: if the paper embeds a choropleth, the map uses disaggregation (41 on CHN polygon + HKG 96 + MAC 128 + TWN 214) while narrative rankings and tables use 351.
faostat_get_rankings HTTP-500 fallback. On failure, reconstruct by pulling faostat_get_data across all reporting countries and sorting client-side. Note the fallback in Methods.

Read the full file on GitHub · 246 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.

2mo ago First seen · 246 lines · 218 tokens per session scan A 1c4da3ff8aab

Subscribe to this mod's changes

faostat-scientific-paper is a skill published in the GitHub repository berba-q/faostat-skills (10 stars, last pushed 6mo ago), licensed MIT. It adds 218 tokens to every session and 4,819 once invoked, about $0.0009 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 2026-08-31.

Claude Code Scientific Writing and docs agriculture ai-skills claude-code-plugin codex faostat

faostat-scientific-paper next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
faostat-scientific-paperberba-q/faostat-skills	Skill	10	6mo ago	MIT	A	218	Claude Code
faostat-guidecyanheads/faostat-mcp-server	Skill	3	5d ago	Apache-2.0	A	49	Claude Code
food-systems-dataxjtulyc/awesome-rosetta-skills	Skill	35	6mo ago	none	A	40	Claude Code, Codex
top-designwondelai/skills	Skill	2.6k	6d ago	MIT	A	113	Claude Code, Codex
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