AC nasa-dataset-download
Download any NASA Earth observation dataset (HDF / NetCDF / GeoTIFF) end-to-end. Wraps the official earthaccess library to authenticate with NASA Earthdata Login and bulk-download granules from MODIS, VIIRS, GPM, Sentinel, SMAP, ASTER, etc. Supports BBox + temporal window filtering and QA sidecars. Default credentials are loaded from ~/.geoskill/secrets.json (NASA Earthdata bearer token). 0.2.0: alias map (description → short_name), multi-word search, --dry-run, proper exit codes (5 on 0 results), accurate --max-files, fixed granule display.
Download any NASA Earth observation dataset (HDF / NetCDF / GeoTIFF) end-to-end.
As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency
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: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 55/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (nasa-dataset-download) differs from the folder (geoskill-nasa-dataset-download)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 28 steps
- 100Execution cost. Instruction body is 2533 tokens
- 100Running it twice. No mutating operations
- low 14 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)
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +3Description length 547: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 28 items
- +3Output format is stated explicitly
- +4Has examples (5 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.