metforge-model-diagnose

metforge-model-diagnose is a skill for Claude Code, Codex from yuanruichen/MetForge. It costs 135 tokens per session (1,295 once invoked), scanned A, original, MIT.

A diagnostic workflow for atmospheric models and dynamical cores, the numerical parts of weather and climate models that calculate motion and fluid behavior.

In plain words
What is it for?
Investigate idealized tests, waves, advection, instability, conservation, error growth, convergence, timestep, resolution, domain, and parallel-computing sensitivity.
Why use it?
It helps turn model output into a testable explanation by comparing configurations with references and separating expected results from suspicious or inconclusive ones.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the metforge plugin — 4 skills shipped together

Good fit Investigate idealized tests, waves, advection, instability, conservation, error growth, convergence, timestep, resolution, domain, and parallel-computing sensitivity.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yuanruichen/metforge/metforge-model-diagnose
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 yuanruichen/MetForge --skill metforge-model-diagnose
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-model-diagnose

README.md
[![agentmods](https://agentmods.dev/badge/skills/yuanruichen/metforge/metforge-model-diagnose.svg)](https://agentmods.dev/skills/yuanruichen/metforge/metforge-model-diagnose)
Your own site
<a href="https://agentmods.dev/skills/yuanruichen/metforge/metforge-model-diagnose"><img src="https://agentmods.dev/badge/skills/yuanruichen/metforge/metforge-model-diagnose.svg" alt="Measured on agentmods" height="20"></a>
Per session 135 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,295 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 $0.00135 $0.01295
Opus 5 $0.00068 $0.00647
Sonnet 5 $0.00027 $0.00259
Haiku 4.5 $0.00014 $0.00129

Measured 7d ago against content hash d07aa0b9c967, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

metforge-model-diagnose 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 7d 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-model-diagnose/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MetForge Model Diagnose

Turn model output into a falsifiable diagnosis. Prefer the next decisive check over a long catalog of generic plots.

Diagnostic workflow

  1. State the test contract:
    • property or mechanism being tested
    • expected solution, symmetry, invariant, or benchmark
    • control and changed factor
    • diagnostic time window and success criterion
    • observation that would falsify the working explanation
  2. Inventory the actual run configuration and outputs. Compare namelists, compiler/precision, solver, grid, timestep, domain, boundary conditions, physics, diffusion, filters, and decomposition before interpreting differences.
  3. Establish the reference. Prefer an analytic solution, converged/high-resolution run, published benchmark, or internally consistent control. Do not call one arbitrary run “truth” without qualification.
  4. Climb the diagnostic ladder below. Stop when the evidence isolates the failure or when the next step requires new data.
  5. Classify each result as expected, numerically suspicious, physically inconsistent, configuration-dependent, or inconclusive.
  6. Produce an evidence table and recommend one next experiment with the largest discrimination value.

Diagnostic ladder

1. Integrity

Check file completeness, coordinates, units, time cadence, NaN/Inf, extrema, restart continuity, and whether the intended code path actually ran.

2. Invariants and equilibrium

Check mass, tracer mass, energy or energy-like quantities, hydrostatic/geostrophic balance residuals, symmetry, uniform-state preservation, and boundary fluxes as appropriate.

3. Error magnitude and growth

Use more than extrema. Select metrics from references/diagnostic-metrics.md, including weighted bias, RMS/L2, maximum norm, drift rate, relative error, pattern correlation, phase displacement, and conservation residual.

4. Structure

Examine the error field, cross-flow components, vertical structure, spectra, wavenumber content, propagation speed, fronts, and symmetry breaking. Scalar norms can miss compensating or phase-shifted errors.

Read the full file on GitHub · 94 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. 7d ago First seen · 94 lines · 135 tokens per session scan A d07aa0b9c967

Subscribe to this mod's changes

metforge-model-diagnose is a skill published in the GitHub repository yuanruichen/MetForge (4 stars, last pushed 25d ago), licensed MIT. It adds 135 tokens to every session and 1,295 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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