SKILLEMALL.ai

BD smyx-orchid-growth-status-detection-analysis

AI-powered orchid growth-status detection from HD images (including roots visible through transparent pots) via orchid cameras or smartphones. Measures new-shoot count, flower-spike length, and root color/condition (white = healthy, brown = aged, black = rotten) to deliver a holistic vitality assessment (vigorous / normal / weak) plus care guidance such as 'three new shoots, healthy roots, increase phosphorus-potassium to promote spike growth'. Helps orchid hobbyists pinpoint repotting and feeding timing. Scenarios: home orchid care, orchid greenhouses, horticulture studios. | 通过兰花栽培专用摄像头或手机拍摄的高清图像(包括透明兰盆内的根系),利用AI视觉分析技术检测兰花新芽萌发数量、花梗(花箭)生长长度以及根系颜色(白色健康、褐色老化、黑色腐烂),综合输出兰花的生长状态评估(旺盛/正常/衰弱)及养护建议(如"新芽萌发3个,根系健康,可适当增加磷钾肥促进花梗生长")。有助于兰花爱好者精准掌握植株生长节奏,及时调整水肥管理。应用场景:兰花家庭养护、兰花大棚、兰花园艺工作室。

ClawHub Agent Skills author: smyx-sunjinhui v1.0.8 MIT-0 30 files body ≈ 1 705 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 35/100 · Unfinished process — weak spots: steps, result and completion, when it triggers

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
D
35/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 30. 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 35/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 25Steps. 1 steps
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1705 tokens
  • 100Running it twice. No mutating operations
  • low 14 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)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • -284 emoji in the instructions: noise for the model
  • -32 of 4 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 785: enough signal without eating the budget
  • +4Structure: 24 headings
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
This orchid analysis skill is mostly coherent, but it silently provisions and reuses a remote identity while storing service tokens locally, which users should review before installing.
LLM: suspicious (high) · 17 Aug 2026