Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/orcaqubits/agentic-commerce-skills-plugins/a2a-clientnpx skills add OrcaQubits/agentic-commerce-skills-plugins --skill a2a-clientgit clone --depth 1 https://github.com/OrcaQubits/agentic-commerce-skills-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/orcaqubits/agentic-commerce-skills-plugins/a2a-client)<a href="https://agentmods.dev/skills/orcaqubits/agentic-commerce-skills-plugins/a2a-client"><img src="https://agentmods.dev/badge/skills/orcaqubits/agentic-commerce-skills-plugins/a2a-client.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00048 | $0.00905 |
| Opus 5 | $0.00024 | $0.00452 |
| Sonnet 5 | $0.00010 | $0.00181 |
| Haiku 4.5 | $0.00005 | $0.00090 |
Grade A, and why
a2a-client scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A2A Client Implementation
Before writing code
Fetch live docs:
- Fetch
https://a2a-protocol.org/latest/specification/for client-side protocol requirements - Web-search
site:github.com a2aproject a2a-python clientora2aproject a2a-js clientfor SDK client classes - Web-search
site:github.com a2aproject a2a-samples clientfor reference client implementations - Fetch the target SDK README for client usage patterns
Conceptual Architecture
What an A2A Client Does
An A2A client is the requesting side that:
- Discovers agents via Agent Cards (fetch
/.well-known/agent-card.json) - Sends messages to create or continue tasks
- Handles synchronous responses or SSE streams
- Manages multi-turn conversations (handles
input-requiredstates) - Optionally configures push notifications for long-running tasks
Client Workflow
1. Discover agent → Fetch Agent Card
2. Check capabilities → Verify the agent can handle the task
3. Authenticate → Satisfy the agent's auth requirements
4. Send message → POST JSON-RPC to agent URL
5. Handle response → Process task result or continue conversation
6. Monitor → Poll, stream, or receive push notifications
Discovery
Before sending requests, the client must discover the target agent:
- Direct URL — Fetch
{base_url}/.well-known/agent-card.json - Registry lookup — Query an agent registry by skill tags or name
- Referral — Another agent provides the target agent's URL
- Configuration — Hard-coded agent URLs for known partners
Sending Messages
Two modes:
- Synchronous (
message/send) — Send a message, wait for the complete response - Streaming (
message/stream) — Send a message, receive SSE events as the agent processes
Client Message Structure
{
"jsonrpc": "2.0",
"method": "message/send",
"id": "request-id",
"params": {
"message": {
"role": "user",
"parts": [
{ "kind": "text", "text": "Your task description" }
]
},
"configuration": {
"acceptedOutputModes": ["text/plain", "application/json"]
}
}
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 108 lines · 48 tokens per session scan A d88772fef5a9
a2a-client is a skill published in the GitHub repository OrcaQubits/agentic-commerce-skills-plugins (39 stars, last pushed 3mo ago), licensed MIT. It adds 48 tokens to every session and 905 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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