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BD aiusd-skill

AIUSD trading and account management skill. Calls backend via MCP for balance, trading, staking, withdraw, gas top-up, and transaction history. Auth priority: MCP_HUB_TOKEN env, then mcporter OAuth or local token file.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files · 1 script body ≈ 2 604 tokens Open the sourcegithub.com↗ analyzed 2 d ago

AIUSD trading and account management skill.

As a process D 44/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, consistency

IntegrationAI and agentstype 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
84/100
safety, quality, tests
Safety 60%
92
Quality 40%
72
Run on models
none yet
Process rating
D
44/100
Unfinished process
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

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Obfuscation 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 files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.

For the author

Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.

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 · 4

✓ No critical or high findings

Medium and low: 4
  • medium Obfuscation obf-base64-blob aiusd-skill-installer.sh:112
    Long base64-looking blob
    H4sI…kAA+y9XW…wF3+zb7G+5fFHDP0z/hzMy/PTwy…nX9+s/ueln…J0b/L/N/Z+UX+
  • low Obfuscation obf-base64-blob aiusd-skill-installer.js:91
    Long base64-looking blob (quoted — discussed, not commanded)
    const PACKAGE_DATA = `H4sI…kAA+y9XW…wF3+zb7G+5fFHDP0z/hzMy/PTwy…nX9+s/ue
    quoted
  • low Secrets in code secret-high-entropy-token aiusd-skill-installer.js:91
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const PACKAGE_DATA = `H4sI…kAA+y9XW…wF3+zb7G+5fFHDP0z/hzMy/PTwy…nX9+s/ue
    quoted
  • low Secrets in code secret-high-entropy-token aiusd-skill-installer.sh:112
    High-entropy token-like string (may be an id, hash or a credential)
    H4sI…kAA+y9XW…wF3+zb7G+5fFHDP0z/hzMy/PTwy…nX9+s/ueln…J0b/L/N/Z+UX+

Files scanned: 5. 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")

Process rating: all ten parameters 44/100

  • 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
  • 40Consistency. Frontmatter name (aiusd-skill) differs from the folder (aiusd)
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
  • 60Steps. 88 steps, 4 vague phrases
  • 100Execution cost. Instruction body is 2604 tokens
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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 218: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 88 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.