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 agentmods add skills/yuanruichen/metforge/metforge-analysisnpx skills add yuanruichen/MetForge --skill metforge-analysisgit clone --depth 1 https://github.com/yuanruichen/MetForgeWrote 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/yuanruichen/metforge/metforge-analysis)<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>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 | $0.00138 | $0.01061 |
| Opus 5 | $0.00069 | $0.00531 |
| Sonnet 5 | $0.00028 | $0.00212 |
| Haiku 4.5 | $0.00014 | $0.00106 |
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.
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
- Inspect files, coordinates, units, calendar, chunking, missing values, and existing project code.
- 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
- Read references/indices-and-diagnostics.md, references/trends-and-filtering.md, or references/statistical-methods.md as the task requires.
- Validate the definition on a small subset or synthetic case with a known result.
- Select direct execution or a scheduler using the rules below, then run the smallest valid calculation before scaling out.
- Validate dimensions, coordinates, units, numeric ranges, sample counts, missing-data propagation, and at least one independent or limiting-case check.
- Save self-describing outputs and append an execution record after each completed computation stage.
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.
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.
- 3d ago First seen · 67 lines · 138 tokens per session scan A cb1af357cd4e
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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