SKILLEMALL.ai

DB testmaibao

(no description)

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: qkainan v1.0.0 MIT-0 5 files body ≈ 185 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 67/100 · Nearly there — weak spots: when it triggers, failures and branches, progress reporting

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
D
49/100
safety, quality, tests
Safety 60%
82
Quality 40%
0
Run on models
none yet
Process rating
B
67/100
Nearly there
When it triggers w 12
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Obfuscation
If you install

The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.

For the author

Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Add a description to the frontmatter: without it the skill never triggers.
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 · 1

  • high Obfuscation uni-zero-width skill.md:25
    Zero-width / invisible characters (possible hidden text) (6 occurrences)
    **␀User:␀** "查一下深圳的天气"

Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger

Process rating: all ten parameters 67/100

  • 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
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. No external tools needed
  • 100Steps. 4 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 185 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 0: 120–800 characters recommended
  • +1No license
  • +2Single-language instructions
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 4 items
  • +3Output format is stated explicitly
  • +4Has examples (0 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: suspicious
This skill is low-risk for privacy and system access, but it advertises real current weather while returning random simulated weather data.
LLM: suspicious (high) · VirusTotal: · 29 May 2026