AB lidar-point-cloud-analysis
Read LAS/LAZ/COPC point clouds, compute statistics, classification QA, DEM/DSM/CHM rasters, cross-sections, density maps, and quality reports. Use when analyzing LiDAR point cloud data, generating terrain models, checking point cloud quality, or producing canopy height models.
Read LAS/LAZ/COPC point clouds, compute statistics, classification QA, DEM/DSM/CHM rasters, cross-sections, density maps, and quality reports.
As a process B 66/100 · 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: 0. 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 66/100
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (lidar-point-cloud-analysis) differs from the folder (geoskill-lidar-point-cloud-analysis)
- 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
- 85Steps. 14 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Execution cost. Instruction body is 1304 tokens
- low 12 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 277: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 14 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.