SKILLEMALL.ai

AB lobster-farm-agent

Play and manage a Lobster Tamagotchi farm game autonomously via browser. Each installed agent gets a unique KEY binding it to its own lobster. The agent acts as the lobster's "brain", making autonomous decisions. Use when the user mentions lobster game, lobster farm, wants to check on their lobster, play the lobster game, manage their virtual lobster pet, or says "帮我玩龙虾游戏", "看看我的龙虾", "龙虾农场", "龙虾MUD", "注册龙虾".

ClawHub Agent Skills author: Jared v1.0.0 MIT-0 8 files body ≈ 2 697 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 69/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
69/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

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

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 69/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 13 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 40 steps
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2697 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 411: enough signal without eating the budget
    • +4Structure: 31 headings
    • +3Step-by-step instructions: 40 items
    • +4Has examples (15 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: suspicious
    This is a disclosed lobster game skill, but it sends user work-pattern telemetry to a raw-IP HTTP server and can act autonomously, so it should be reviewed before installation.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026