SKILLEMALL.ai

AC geoskill-pest-disease-detection

基于红边异常、热红外温度、纹理变化与多时相早期胁迫检测,识别疑似病虫害区域。Detects suspected pest/disease areas from red-edge anomaly, thermal, texture and multi-temporal early stress.

ClawHub Agent Skills author: ruiduobao v1.0.0 MIT-0 25 files body ≈ 515 tokens Open the sourceclawhub.ai analyzed 3 d ago

基于红边异常、热红外温度、纹理变化与多时相早期胁迫检测,识别疑似病虫害区域。Detects suspected pest/disease areas from red-edge anomaly, thermal, texture and multi-temporal early stress.

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 20. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 62/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 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
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. No external tools needed
  • 100Steps. 4 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 515 tokens
  • 100Running it twice. No mutating operations
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • 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 147: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 4 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
The main pest-detection script is mostly local and coherent, but the package also ships undisclosed credential and network helper code, including hardcoded Earthdata credentials, that does not fit the stated offline purpose.
LLM: suspicious (high) · 4 Aug 2026