metforge-analysis

metforge-analysis is a skill for Claude Code, Codex from yuanruichen/MetForge. It costs 138 tokens per session (1,061 once invoked), scanned A, original, MIT.

A toolkit for analysing atmospheric and climate data with reproducible calculations and statistical tests.

In plain words
What is it for?
Use it to calculate climate indices, derive weather variables, analyse trends, filter time series, run PCA or EOF analysis, and perform regressions or significance tests.
Why use it?
It makes the formulas, units, assumptions, missing-data rules, and validation checks visible so scientific results can be reviewed and repeated.

Skill for Claude CodeCodex

Part of the metforge plugin — 4 skills shipped together

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.

agentmods
npx agentmods add skills/yuanruichen/metforge/metforge-analysis
Any agent
npx skills add yuanruichen/MetForge --skill metforge-analysis
Clone the repo
git clone --depth 1 https://github.com/yuanruichen/MetForge

Made for: Claude Code, Codex.

Or install metforge, the plugin that ships this one along with the rest of its 4 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.

agentmods badge for metforge-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/yuanruichen/metforge/metforge-analysis.svg)](https://agentmods.dev/skills/yuanruichen/metforge/metforge-analysis)
Your own site
<a href="https://agentmods.dev/skills/yuanruichen/metforge/metforge-analysis"><img src="https://agentmods.dev/badge/skills/yuanruichen/metforge/metforge-analysis.svg" alt="Measured on agentmods" height="20"></a>
Per session 138 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,061 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00138 $0.01061
Opus 5 $0.00069 $0.00531
Sonnet 5 $0.00028 $0.00212
Haiku 4.5 $0.00014 $0.00106

Measured 3d ago against content hash cb1af357cd4e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

metforge-analysis 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 3d 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/metforge-analysis/SKILL.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MetForge Analysis

Turn atmospheric data into a traceable scientific diagnostic. Make the mathematical definition, sampling assumptions, units, execution mode, and validation visible.

Analysis contract

Before computing, establish:

  • scientific quantity or hypothesis
  • exact formula, published definition, or package function
  • variables, units, coordinates, domain, levels, period, season, and baseline
  • weighting, anomaly, standardization, missing-data, and event-selection rules
  • output variables, dimensions, units, metadata, and acceptance checks

Do not silently choose among competing index definitions. For a named index, recover the authoritative definition and identify any required reference EOFs, climatology, or external coefficients.

Computation workflow

  1. Inspect files, coordinates, units, calendar, chunking, missing values, and existing project code.
  2. Choose an established implementation before writing formulas:
    • use MetPy with unit-aware inputs for supported meteorological diagnostics
    • use xarray for labeled reductions, grouping, rolling, resampling, and alignment
    • use SciPy/statsmodels for filters and statistical models
    • use xclim for supported climate indices and xeofs/eofs for EOF analysis
    • use xskillscore or established statistical libraries for supported metrics
  3. Read references/indices-and-diagnostics.md, references/trends-and-filtering.md, or references/statistical-methods.md as the task requires.
  4. Validate the definition on a small subset or synthetic case with a known result.
  5. Select direct execution or a scheduler using the rules below, then run the smallest valid calculation before scaling out.
  6. Validate dimensions, coordinates, units, numeric ranges, sample counts, missing-data propagation, and at least one independent or limiting-case check.
  7. Save self-describing outputs and append an execution record after each completed computation stage.

Read the full file on GitHub · 67 lines

Files

What ships with it

4 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.

  1. 3d ago First seen · 67 lines · 138 tokens per session scan A cb1af357cd4e

Subscribe to this mod's changes

metforge-analysis is a skill published in the GitHub repository yuanruichen/MetForge (4 stars, last pushed 22d ago), licensed MIT. It adds 138 tokens to every session and 1,061 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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