SKILLEMALL.ai

BB greenhelix-agent-interoperability-bridge

The Agent Interoperability Bridge: Connecting GreenHelix Agents to x402, ACP, A2A, MCP, Visa TAP, Google AP2/UCP, PayPal Agent Ready, and OpenAI ACP Ecosystems. Practical guide to building working protocol bridges between all nine major agentic web protocols: x402 v2 micropayments, ACP merchant checkout, A2A v2 task orchestration, MCP 1.5+ tool integration, Visa TAP card-network payments, Google AP2 real-time payments, UCP service orchestration, PayPal Agent Ready, and OpenAI ACP commerce flows. Includes detailed code examples with Python bridge classes for protocol translation, cross-protocol identity mapping, intelligent payment routing, and event bri

ClawHub Agent Skills author: mirni v1.3.1 MIT-0 2 files body ≈ 35 761 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, execution cost

IntegrationAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Execution cost w 6
10
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 0

✓ No critical or high findings

Files scanned: 2. 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")
  • warning body-long SKILL.md body ≈ 35761 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "type"
  • note frontmatter-key unknown frontmatter key "price_usd"
  • note frontmatter-key unknown frontmatter key "content_type"
  • note frontmatter-key unknown frontmatter key "executable"
  • note frontmatter-key unknown frontmatter key "install"
  • note frontmatter-key unknown frontmatter key "credentials"

Process rating: all ten parameters 65/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 10Execution cost. Instruction body is 35761 tokens: crowds the task out of the window
  • 20When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 100Steps. 76 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Failures and branches. 9 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 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
  • low 17 top-level sections: this looks like several domains in one skill

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)
  • +2Single-language instructions
  • +3Description length 661: enough signal without eating the budget
  • +4Structure: 65 headings
  • +3Step-by-step instructions: 76 items
  • +3Output format is stated explicitly
  • +4Has examples (24 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This is a non-executable guide, but its payment-bridge examples include under-scoped flows that could lead to unauthorized charges or broken escrow handling if copied into production.
LLM: suspicious (high) · VirusTotal: · 29 May 2026