SKILLEMALL.ai

AB zhentan

Zhentan is your personal onchain security agent and co-signer. It monitors pending multisig transactions, screens them against behavioral patterns and security risk data, and auto-signs safe ones — blocking or flagging suspicious activity before it executes. Use when the user wants to review pending transactions, approve or reject a transaction, check risk scores, toggle screening mode, view transaction history, or queue and process an invoice.

ClawHub Agent Skills author: koshikraj v1.0.2 MIT-0 2 files body ≈ 2 486 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 68/100 · Nearly there — weak spots: result and completion, inputs and preconditions

AnalyzerAI and agentsFinanceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
95
Quality 40%
84
Run on models
none yet
Process rating
B
68/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
30
Tools and files w 18
60
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Exfiltration net-credential-use SKILL.md:117
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill; the skill's own vendor host)
      curl -s -H "Authorization: Bearer $AGENT_SECRET" "https://api.zhentan.me/status?safe=…"
      security skillvendor-host
    • low Exfiltration net-credential-use SKILL.md:120
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill; the skill's own vendor host)
      curl -s -H "Authorization: Bearer $AGENT_SECRET" "https://api.zhentan.me/transactions?safeAddress=…"
      security skillvendor-host
    • low Exfiltration net-credential-use SKILL.md:126
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill; the skill's own vendor host)
      curl -s -H "Authorization: Bearer $AGENT_SECRET" "https://api.zhentan.me/status?safe=…"
      security skillvendor-host
    • low Exfiltration net-credential-use SKILL.md:169
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill; the skill's own vendor host)
      curl -s -H "Authorization: Bearer $AGENT_SECRET" "https://api.zhentan.me/transactions/tx-XXX"
      security skillvendor-host

    A further 1 matches are quotations in this security skill's documentation and are not counted as findings.

    Files scanned: 2. 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 68/100

    • 0Result and completion. Does not say what the result is
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 30 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2486 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 448: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 30 items
    • +4Has examples (21 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    Zhentan is a coherent crypto security co-signer, but it gives chat-driven authority to execute on-chain transactions and change security controls without enough visible safeguards.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026