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.
npx skills add berba-q/faostat-skills --skill exploregit clone --depth 1 https://github.com/berba-q/faostat-skillsWrote 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.
[](https://agentmods.dev/skills/berba-q/faostat-skills/explore)<a href="https://agentmods.dev/skills/berba-q/faostat-skills/explore"><img src="https://agentmods.dev/badge/skills/berba-q/faostat-skills/explore/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.
<a href="https://agentmods.dev/skills/berba-q/faostat-skills/explore"><img src="https://agentmods.dev/badge/skills/berba-q/faostat-skills/explore.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00103 | $0.01474 |
| Opus 5.5 | $0.00041 | $0.00590 |
| Sonnet 5.5 | $0.00021 | $0.00295 |
| Haiku 4.5 | $0.00010 | $0.00147 |
Grade A, and why
faostat-explore 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.
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.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FAOSTAT Explorer
Guided discovery of FAOSTAT's data catalog. Help users understand what data is available, browse domains, see sample data, and find the right starting point for their analysis.
Prerequisites
Before starting, confirm the FAOSTAT MCP tools are available by checking that tools faostat_list_groups, faostat_list_domains, faostat_get_dimensions, faostat_get_data, and faostat_get_metadata are accessible. If they are not, inform the user that this skill requires the FAOSTAT MCP server to be connected and stop.
Workflow
Step 1 — Understand the User's Interest
Ask the user: "What topic are you interested in exploring?" Examples:
- A subject area: "fisheries", "fertilizers", "food prices", "livestock", "trade"
- A question: "What data does FAO have about rice production?"
- A broad theme: "climate and agriculture", "food security in Africa"
- Or just: "Show me what's available" (full catalog overview)
If the user provides their interest in their initial message, proceed without re-asking.
Step 2 — Map the FAOSTAT Catalog
Call faostat_list_groups(lang='en') to retrieve all domain groups in FAOSTAT.
Present the groups to the user in a clear, organized list. FAOSTAT organizes data into groups such as:
- Production
- Trade
- Food Security
- Food Balances
- Prices
- Inputs
- Population
- Investment
- Macro-Statistics
- Emissions (Agriculture, Land Use, Forestry)
- Climate Change
- and more
If the user gave a specific topic, identify which group(s) are most relevant. If the user asked for a full overview, present all groups briefly.
Step 3 — Drill Into Relevant Domain Groups
For each relevant group, call faostat_list_domains(group_code, lang='en') to list the specific domains within that group.
Present the domains with their codes and descriptions. For example, within the Production group:
- QCL — Crops and Livestock Products
- QI — Production Indices
- etc.
If the user's topic spans multiple groups, show domains from all relevant groups.
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.
- 1mo ago First seen · 124 lines · 103 tokens per session scan A 2655792746c7
faostat-explore is a skill published in the GitHub repository berba-q/faostat-skills (9 stars, last pushed 6mo ago), licensed MIT. It adds 103 tokens to every session and 1,474 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 2026-08-31.
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