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AB fluxa-agent-wallet

FluxA Agent Wallet integration via CLI. Enables agents to make x402 payments for paid APIs, send USDC payouts to any wallet, and create payment links to receive payments. Use when the user asks about crypto payments, x402, USDC transfers, payment links, or interacting with the FluxA Agent Wallet.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files body ≈ 1 590 tokens Open the sourcegithub.com↗ analyzed 2 d ago

FluxA Agent Wallet integration via CLI.

As a process B 74/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

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
A
94/100
safety, quality, tests
Safety 60%
98
Quality 40%
87
Run on models
none yet
Process rating
B
74/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token scripts/fluxa-cli.bundle.js:469
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      var DEFAULT_ASSET = "0x83…913";
      quoted
    • low Secrets in code secret-high-entropy-token X402-PAYMENT.md:115
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      PAYLOAD_402='{"accepts":[{"scheme":"exact","network":"base","maxAmountRequired":"10000","asset":"0x83…913","payTo":"0xFf…CD3","resou
      quoted

    Files scanned: 5. 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 74/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 17 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 8 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1590 tokens

    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 297: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 8 items
    • +4Has examples (9 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.