SKILLEMALL.ai

AC earthquake-damage-assessment

震后损害快速评估 — 利用震前震后 SAR/光学变化和建筑道路暴露,快速筛查疑似建筑损毁、 道路阻断和受影响人口。支持相干性/后向散射/纹理/光谱多特征融合,对象级聚合, 损毁概率分级与人工复核任务生成。

ClawHub Agent Skills author: ruiduobao v2.0.0 MIT-0 6 files body ≈ 806 tokens Open the sourceclawhub.ai analyzed 2 d ago

震后损害快速评估 — 利用震前震后 SAR/光学变化和建筑道路暴露,快速筛查疑似建筑损毁、 道路阻断和受影响人口。支持相干性/后向散射/纹理/光谱多特征融合,对象级聚合, 损毁概率分级与人工复核任务生成。

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency

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
63/100
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: 6. 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 63/100

  • 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
  • 40Consistency. Frontmatter name (earthquake-damage-assessment) differs from the folder (geoskill-earthquake-damage-assessment)
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Steps. 24 steps
  • 100Execution cost. Instruction body is 806 tokens
  • 100Running it twice. No mutating operations

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)
  • +3Description length 102: 120–800 characters recommended
  • +2Single-language instructions
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 24 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

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

External checks

ClawHub: suspicious
This skill does not look intentionally harmful, but it can generate earthquake damage reports from synthetic data even when real inputs or downloads are supplied, so it needs review before use.
LLM: suspicious (high) · 31 Jul 2026