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BD cold-chain-risk-calculator

Calculate cold chain transport risks

ClawHub Hermes author: AIpoch v0.1.0 MIT-0 3 files body ≈ 537 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 47/100 · Unfinished process — weak spots: result and completion, when it triggers, failures and branches

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
D
47/100
Unfinished process
Result and completion w 14
0
When it triggers w 12
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "status"
  • note frontmatter-key unknown frontmatter key "risk_level"
  • note frontmatter-key unknown frontmatter key "skill_type"
  • note frontmatter-key unknown frontmatter key "owner"
  • note frontmatter-key unknown frontmatter key "reviewer"
  • note frontmatter-key unknown frontmatter key "last_updated"

Process rating: all ten parameters 47/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (cold-chain-risk-calculator) differs from the folder (cold-chain-risk-calculator-2)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 25 steps
  • 100Execution cost. Instruction body is 537 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

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 36: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (1 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

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

External checks

ClawHub: clean
This skill is a simple local cold-chain risk calculator with no evidence of network access, credential use, persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026