AB groundwater-recharge-potential
Multi-criteria screening of groundwater recharge potential using terrain, soil, geology, land cover, drainage density, and rainfall. Supports AHP, weighted overlay, and fuzzy aggregation with sensitivity analysis and spatial validation. Use when the user wants to identify zones with higher recharge potential, compare weight scenarios, or generate candidate recharge area maps for planning purposes.
Multi-criteria screening of groundwater recharge potential using terrain, soil, geology, land cover, drainage density, and rainfall.
As a process B 70/100 · Nearly there — weak spots: failures and branches, consistency, running it twice
How to improve
- 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
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 70/100
- 0Failures and branches. Linear process with no failure handling
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (groundwater-recharge-potential) differs from the folder (geoskill-groundwater-recharge-potential)
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 55 steps
- 100Execution cost. Instruction body is 1332 tokens
- 100Progress reporting. Reports progress
- low 13 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 400: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 55 items
- +3Output format is stated explicitly
- +4Has examples (3 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.