SKILLEMALL.ai

BF Design_Daily

Daily design industry brief for UI/UX designers and PMs. Covers AI × design, design engineering, top product experience breakdowns, and design decision logic. Triggers: 'design brief', '设计日报', '今日设计', '设计早报', 'design news today'

ClawHub Agent Skills author: Jack James v1.0.2 MIT-0 8 files body ≈ 434 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process F 34/100 · Will not run — weak spots: steps, result and completion, when it triggers

ProcedureInfrastructureDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
94
Quality 40%
64
Run on models
none yet
Process rating
F
34/100
Will not run
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Dangerous commands cmd-eval-dynamic setup.py:547
    Dynamic code execution from decoded/untrusted input
    os.system(f"{sys.executable} {BASE_DIR / 'run.py'}")
  • low Dangerous commands cmd-cron-mention setup.py:407
    Mentions editing / listing crontab (string literal in code, not executed)
    {BOLD}crontab -e{RESET}
    code literal

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "requires"

Process rating: all ten parameters 34/100

  • 0Steps. Prose only: no discrete steps
  • 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
  • 40Consistency. Frontmatter name (Design_Daily) differs from the folder (design-daily)
  • 100Tools and files. No external tools needed
  • 100Execution cost. Instruction body is 434 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)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 228: enough signal without eating the budget
  • +4Structure: 10 headings
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This skill appears to do what it claims: fetch design news, summarize it with Serper and DeepSeek, and save local brief outputs.
LLM: benign (high) · VirusTotal: · 29 May 2026