SKILLEMALL.ai

BF plant-growth-stage-recognition-analysis

Accurately identifies key growth stages of plants from germination to fruiting based on computer vision and deep learning, provides structured data for precision agriculture decision support. | 植物生长阶段识别技能,基于计算机视觉与深度学习算法,精准识别植物从发芽到结果的全生命周期关键生长阶段,为精准农业提供科学决策支持

ClawHub Agent Skills author: smyx-sunjinhui v1.0.13 MIT-0 29 files body ≈ 1 411 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 19/100 · Will not run — References files that are not bundled: references/api_doc.md

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
59
Run on models
none yet
Process rating
F
19/100
Will not run
References files that are not bundled: references/api_doc.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 29. 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")
  • warning missing-ref reference to a missing file: references/api_doc.md

Process rating: all ten parameters 19/100

Will not run. References files that are not bundled: references/api_doc.md
  • 0Tools and files. 1 referenced file(s) missing: references/api_doc.md
  • 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
  • 40Consistency. Frontmatter name (plant-growth-stage-recognition-analysis) differs from the folder (smyx-plant-growth-stage-recognition-analysis)
  • 100Execution cost. Instruction body is 1411 tokens
  • 100Running it twice. No mutating operations
  • 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)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • -255 emoji in the instructions: noise for the model
  • -32 of 4 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 258: enough signal without eating the budget
  • +4Structure: 20 headings
  • +4Has examples (3 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.

External checks

ClawHub: suspicious
The plant-analysis feature is real, but the skill silently manages identity and tokens and is configured to send media and credentials over cleartext HTTP despite claiming HTTPS.
LLM: suspicious (high) · 9 Sept 2026