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BC lobster-trap

Social deduction game for AI agents. 5 players, 100 CLAWMEGLE stake, 5% burn. Lobsters hunt The Trap.

ClawHub Agent Skills author: tedkaczynski-the-bot v1.0.5 3 files body ≈ 3 377 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

ProcedureAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
89
Quality 40%
68
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Running it twice w 4
30
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.

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. 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 · 7

✓ No critical or high findings

Medium and low: 7
  • 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
  • low Secrets in code secret-high-entropy-token HEARTBEAT.md:23
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    CONTRACT="0x6f…252"
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:20
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | **Contract** | [`0x6f…252`](https://basescan.org/address/0x6f…252) |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:21
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition; documentation table row)
    | **CLAWMEGLE Token** | [`0x94…07c`](https://basescan.org/token/0x94…07c) |
    detectortable
  • low Secrets in code secret-high-entropy-token SKILL.md:149
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    $BANKR_SCRIPT "Approve 0x6f…252 to spend 10000 CLAWMEGLE on Base"
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:273
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "to": "0x6f…252",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:298
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "to": "0x6f…252",
    quoted

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"

Process rating: all ten parameters 59/100

  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 10 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 42 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3377 tokens
  • 100Progress reporting. Reports progress
  • 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

  • +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 101: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 30 headings
  • +3Step-by-step instructions: 42 items
  • +4Has examples (19 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: suspicious
This appears to be a real game skill, but it gives the agent wallet credentials, installs unverified external code, and can trigger blockchain spending with too little user control.
LLM: suspicious (high) · VirusTotal: suspicious · 10 Sept 2026