SKILLEMALL.ai

BC antalpha-ai-setup

Install and configure the Antalpha Skills MCP server. Provides 146+ Web3 tools for DEX swaps, smart money tracking, Polymarket prediction markets, Hyperliquid perpetuals, CEX trading, Bitcoin mining, and DeFi analytics.

ClawHub Agent Skills author: bevanding v2.0.0 MIT-0 3 files body ≈ 3 051 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, when it triggers, progress reporting

ProcedureAI and agentsInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
98
Quality 40%
71
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

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
  • low Secrets in code secret-password-literal README.md:30
    Hard-coded password / key literal (may be an example) (placeholder value)
    ✓ api_key: "sk_4…c9d"
    placeholder
  • low Secrets in code secret-password-literal README.md:106
    Hard-coded password / key literal (may be an example) (placeholder value)
    ✓ api_key: "sk_4…c9d"
    placeholder

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 64/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 27 steps
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3051 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 219: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 27 items
  • +4Has examples (3 code blocks)

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

External checks

ClawHub: suspicious
This setup skill is coherent, but it gives an AI agent broad wallet and trading capabilities without enough documented safety and credential boundaries.
LLM: suspicious (high) · VirusTotal: · 29 May 2026