SKILLEMALL.ai

AC worldclim-extract

Extract bioclimatic variables (BIO1-BIO19) from WorldClim GeoTIFF rasters using sample coordinates (longitude/latitude). Supports automatic download of WorldClim 2.1 data, batch extraction from Excel/CSV, and output to Excel or CSV. Use when matching geographic sample points to climate data like annual temperature or precipitation.

ClawHub Agent Skills author: Dong Zhao v1.0.0 MIT-0 3 files · 1 script body ≈ 1 807 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Extract bioclimatic variables (BIO1-BIO19) from WorldClim GeoTIFF rasters using sample coordinates (longitude/latitude).

As a process C 60/100 · Has gaps — weak spots: when it triggers, failures and branches, running it twice

IntegrationExcelData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
60/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 3. 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 60/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1807 tokens
    • low 10 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 333: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 12 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill is a straightforward WorldClim data extraction helper, with expected local file processing and disclosed dataset downloads.
    LLM: benign (high) · VirusTotal: · 16 Sept 2026