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Agent payment infrastructure on Base. Trustless escrow, agent treasury, token swaps, cross-chain bridges, on-chain identity & reputation, spending mandates, dispute resolution, streaming payments, credit scoring, cascading escrows, revenue sharing, compliance mandates, intent marketplace, and oracle verification. Use the hosted MCP server (paylobster.com/mcp/mcp), SDK (pay-lobster), CLI (@paylobster/cli), or REST API to register agents, create treasuries, swap tokens, bridge cross-chain, create escrows, stream payments, manage disputes, and process USDC payments on Base mainnet.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 3 355 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Agent payment infrastructure on Base.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI 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
91/100
safety, quality, tests
Safety 60%
95
Quality 40%
84
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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 Secrets in code secret-high-entropy-token SKILL.md:341
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | Identity Registry | `0xA1…662` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:342
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | Reputation | `0x02…b29` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:343
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | Credit System | `0xD9…0E1` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:344
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | Escrow V3 | `0x49…806` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:350
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | PolicyRegistry | `0x20…0F2` |
      table

    Files scanned: 1. 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 51/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 11 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 6 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3355 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 585: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (13 code blocks)

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