Borrowing it
Nothing to install: this file belongs to a2aproject/a2a-tck. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/a2aproject/a2a-tck/main/.agents/skills/a2a-python-sut/SKILL.mdgit clone --depth 1 https://github.com/a2aproject/a2a-tckWrote 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/a2aproject/a2a-tck/a2a-python-sut)<a href="https://agentmods.dev/skills/a2aproject/a2a-tck/a2a-python-sut"><img src="https://agentmods.dev/badge/skills/a2aproject/a2a-tck/a2a-python-sut/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/a2aproject/a2a-tck/a2a-python-sut"><img src="https://agentmods.dev/badge/skills/a2aproject/a2a-tck/a2a-python-sut.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00052 | $0.02467 |
| Opus 5.5 | $0.00021 | $0.00987 |
| Sonnet 5.5 | $0.00010 | $0.00493 |
| Haiku 4.5 | $0.00005 | $0.00247 |
Grade C, and why
a2a-python-sut scanned grade C with 2 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 2mo 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -s http://localhost:9999/.well-known/agent-card.json | python3 -m json.tool Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
allowed-tools: Bash(make:*) Bash(uv:*) Bash(python:*) Bash(python3:*) Bash(curl:*) Bash(kill:*) Bash(lsof:*) Bash(pkill:*) Read Edit Write Glob Grep Agent How it starts
The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Work with the a2a-python SUT
The a2a-python SUT is a Python application generated from Gherkin .feature files in scenarios/. It implements the A2A protocol using the a2a-python SDK (a2a-sdk) and serves as a conformance target for TCK tests.
Architecture overview
scenarios/*.feature → codegen (parser + steps + python_emitter) → sut/a2a-python/
- Gherkin scenarios (
scenarios/*.feature) define SUT behavior via messageId prefix matching - Code generator (
codegen/) parses.featurefiles and emits a Python project - Jinja2 templates (
codegen/a2a-python/*.j2) producesut_agent.pyandpyproject.toml - Generated output (
sut/a2a-python/) is a complete runnable Python project
Key generated files
| File | Template | Purpose |
|---|---|---|
sut_agent.py |
sut_agent.py.j2 |
Main entry point; TckAgentExecutor with messageId-prefix routing, agent card, and server setup for all three transports |
pyproject.toml |
pyproject.toml.j2 |
Project config with a2a-sdk dependency (installed from local path) |
How the executor works
The generated TckAgentExecutor matches on the messageId prefix from incoming messages:
if message_id.startswith('tck-complete-task'):
await updater.complete(updater.new_agent_message([Part(text="Hello from TCK")]))
return
The TCK tests use tck_id("complete-task") which generates tck-complete-task-<session_hex>, matching the prefix.
Server architecture
The SUT runs all three transports in a single process:
- JSON-RPC via
A2AStarletteApplication(Starlette) - HTTP+JSON via
A2ARESTFastAPIApplication(FastAPI mounted on the Starlette app) - gRPC via
GrpcHandler(grpc.aio server on a separate port)
Step 0: Inform the user of the version of a2a-python
The a2a-python SDK version is controlled by the A2A_PYTHON_SDK_VERSION environment variable.
The default value is defined in codegen/python_emitter.py (_DEFAULT_A2A_PYTHON_SDK_VERSION).
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.
- 2mo ago First seen · 226 lines · 52 tokens per session scan C 4601ee4feb2f
a2a-python-sut is a skill published in the GitHub repository a2aproject/a2a-tck (56 stars, last pushed 8d ago), licensed Apache-2.0. It adds 52 tokens to every session and 2,467 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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