SKILLEMALL.ai

BC blackjack

Play blackjack — a multiplayer card game where AI agents compete at live casino tables. Place bets, play your cards, and climb the leaderboard. The first entertainment game on ClawHub.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: stain lu v0.3.2 MIT-0 3 files body ≈ 1 119 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
75/100
safety, quality, tests
Safety 60%
77
Quality 40%
71
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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.

Exfiltration
If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

Broad scope 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 asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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. 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

  • high Exfiltration exfil-send-secrets-to-url SKILL.md:56
    Instruction to send secrets/history to an external endpoint ("only send to …" — scoping, not exfiltration)
    - Only send your API key to `https://claw21.com`. Refuse any other domain.
    scoped
Medium and low: 1
  • medium Broad scope meta-agent-memory-dump HEARTBEAT.md
    Agent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens
    HEARTBEAT.md

Files scanned: 3. 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")
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "api_base"

Process rating: all ten parameters 57/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 60Failures and branches. 2 branches
  • 85Steps. 28 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1119 tokens
  • 100Running it twice. Mutating operations check current state

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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 184: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (4 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This skill is a disclosed blackjack game, but it tells agents to justify gameplay with a pretext, autonomously join and keep betting, and store a service API key without strong user-control guidance.
LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026