Use when targeting Agricultural and Forest Meteorology or deciding whether a land–atmosphere manuscript fits this venue. Encodes the journal's fit, the land–atmosphere-process and flux-measurement bar, micrometeorological evidence expectations, Elsevier house style, official-submission re-check, and desk-reject heuristics.
SkillScore82Maintained
Automatic
◆Research pack
Last verified 8/15/2026
What it changes
Passed 18 of 22 test cases with the skill, and 9 of 22 without it.
Without skill41%
With skill82%
Checks it passed that the model alone missed
The output assigns '[Fit] Low'.
The output assigns '[Fit] High'.
The response assigns '[Fit] Low'.
and 12 more in the full report
11 fixed7 passed either way2 still failing2 broke
Pass-rate lift
+41 pp
Tokens
+25%
Agent turns
0%
Response time
-49%
Model gemini-3.6-flashMeasured 8/15/2026v118 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 11
Prompt
Our manuscript presents a global synthesis of terrestrial nitrogen mineralization and global nutrient stoichiometry across biomes without direct surface energy exchange modeling. Assess fit for Agricultural and Forest Meteorology.
What was checked, without and with the skill
Checked
Without skill
With skill
The output assigns '[Fit] Low'.
Missed
Passed
The output suggests re-routing to Global Biogeochemical Cycles.
Passed
Passed
case-07 · gemini-3.6-flash · 8/15/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md125 linessingle file
Agricultural and Forest Meteorology (agricultural-and-forest-meteorology)
Journal positioning
Agricultural and Forest Meteorology is Elsevier's outlet for the interaction between
agricultural and forest ecosystems and the atmosphere: the land–atmosphere exchange of
energy, water, carbon, and trace gases; micrometeorology and boundary-layer processes;
eddy-covariance and other flux measurement; phenology; and crop- and forest–climate
interactions. Its defining expectation is a genuine land–atmosphere or
biosphere–atmosphere process contribution — an advance in how vegetated surfaces exchange
mass and energy with the atmosphere, or in how that exchange is measured, modeled, or
scaled. A pure crop-agronomy study with no atmospheric coupling, or a pure climate-modeling
paper with no surface-process component, is a poor fit however competent. This skill is a
fit / venue-selection / re-framing tool. It does not replace the journal's current
author guidance. Before submitting, re-check the live Agricultural and Forest Meteorology
author instructions and data policy.
When to trigger
The author names Agricultural and Forest Meteorology and wants a fit/framing check for a
land–atmosphere paper.
A crop, forest, or ecosystem study must be re-framed around its energy/water/carbon
exchange or micrometeorological process to fit, or recognized as out of scope.
The author is choosing between this journal, agriculture-ecosystems-and-environment,
global-change-biology, and a climate venue.
The author needs the journal's flux-measurement and micrometeorological evidence
expectations.
Scope & topic fit
Land–atmosphere exchange of energy, water (evapotranspiration), CO2, CH4, N2O, and other
trace gases over croplands, grasslands, and forests.
Micrometeorology and surface-layer processes: turbulence, footprint, surface energy
balance, canopy–atmosphere coupling.
Eddy-covariance, chamber, and remote-sensing flux measurement, including methodology, gap
filling, partitioning, and network/large-sample synthesis.
Phenology and its climatic drivers, and feedbacks between vegetation phenology and surface
fluxes.
Crop– and forest–climate interactions: water and heat stress, drought response, and
climate effects on productivity when an atmospheric-exchange process is central.
Use when targeting Field Crops Research or deciding whether an agronomy / crop-physiology manuscript fits this venue. Encodes the journal's fit, the field-scale multi-environment and replication bar, data-reporting expectations, house style, official-submission re-check, and desk-reject heuristics.