ensaio

ensaio is a skill for Claude Code, Codex from SteadfastAsArt/geoscience-skills. It costs 52 tokens per session (603 once invoked), scanned A, original, MIT.

A Python tool for downloading versioned Fatiando geoscience datasets and returning verified local file paths. It records hashes, citations and data conventions so the original downloaded files can be distinguished from derived results.

In plain words
What is it for?
Use it to fetch supported datasets such as GPS data, check their hashes and licences, preserve the source files, and open them with an appropriate format library.
Why use it?
It makes sample-data acquisition reproducible and helps detect incomplete or altered downloads. It also avoids treating a file path as if it were already a table ready for analysis.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to fetch supported datasets such as GPS data, check their hashes and licences, preserve the source files, and open them with an appropriate format library.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/steadfastasart/geoscience-skills/ensaio
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 SteadfastAsArt/geoscience-skills --skill ensaio
Clone the repo
git clone --depth 1 https://github.com/SteadfastAsArt/geoscience-skills

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin ensaio — /plugin install ensaio after adding the marketplace above.

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 ensaio

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/steadfastasart/geoscience-skills/ensaio"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/ensaio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 603 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 $0.00052 $0.00603
Opus 5.5 $0.00021 $0.00241
Sonnet 5.5 $0.00010 $0.00121
Haiku 4.5 $0.00005 $0.00060

Measured 1mo ago against content hash b4952b1c8f76, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ensaio 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.

ensaio/SKILL.md · 62 lines

How it starts

The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ensaio

Retrieve an explicit data version, then read it with a suitable format library. A package version and a dataset version identify different things.

Acquisition

Select a fetcher from the installed API, review the original data license and citation, and estimate download/storage needs. ENSAIO_DATA_DIR selects a project cache. Preserve original downloaded bytes; write derived products elsewhere. The underlying Pooch registry verifies the expected content hash.

Versioned GPS data

# example: alps-gps
from pathlib import Path
import hashlib
import ensaio
import pandas as pd

source_path = Path(ensaio.fetch_alps_gps(version=1))
source_sha256 = hashlib.sha256(source_path.read_bytes()).hexdigest()
gps = pd.read_csv(source_path)

This returns a compressed CSV path, not a DataFrame. A first fetch requires network access unless the verified bytes are already cached. A network failure is not a validated empty dataset, and disabling hash verification is not a fix.

Scientific checks

Inspect column units, coordinate/velocity reference frames, epochs and uncertainty definitions from the original source. For this dataset, the published solution uses IGb08/ITRF2008 and the GRS80 ellipsoid, with horizontal velocities relative to Eurasia. Ensaio's short fetcher description says WGS84; do not use that shorthand to override the detailed source provenance or perform an unrecorded conversion.

Check station identifiers and missing values; keep velocity components and their standard deviations paired. Position uncertainty and velocity uncertainty are not interchangeable. Resampling or gridding must carry the reference frame and does not improve the observation accuracy automatically.

Record dataset version, source hash, package version, retrieval date and citation. See the fetcher documentation, original data and redistributed v1 release.

Read the full file on GitHub · 62 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 · 62 lines · 52 tokens per session scan A b4952b1c8f76

Subscribe to this mod's changes

ensaio is a skill published in the GitHub repository SteadfastAsArt/geoscience-skills (70 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 603 once invoked, about $0.0002 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 2026-09-16.

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