BC netcdf-toolkit
Convert NetCDF/HDF files to GeoTIFF, extract variables, subset by time description: 'Convert NetCDF/HDF files to GeoTIFF, extract variables, subset by time and spatial bbox, and inspect file metadata. All processing is local — no data is uploaded.
Convert NetCDF/HDF files to GeoTIFF, extract variables, subset by time description: 'Convert NetCDF/HDF files to GeoTIFF, extract variables, subset by time…
As a process C 63/100 · Has gaps — weak spots: when it triggers, consistency, progress reporting
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Unexpected scalar at node end at line 2, column 100: …ariables, subset by time description: 'Convert NetCDF/HDF files to GeoTIFF, ex… ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 63/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (netcdf-toolkit) differs from the folder (geoskill-netcdf-toolkit)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 69 steps
- 100Execution cost. Instruction body is 2459 tokens
- 100Running it twice. No mutating operations
- low 11 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +2Single-language instructions
- +3Description length 248: enough signal without eating the budget
- +4Structure: 42 headings
- +3Step-by-step instructions: 69 items
- +3Output format is stated explicitly
- +4Has examples (13 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.