a2a-python is a Python SDK for building software agents that communicate through the Agent2Agent protocol, including running them as A2A servers. It is for developers creating agentic applications and clients or servers that use JSON-RPC, HTTP/REST, or gRPC. The catalogue add-on supports workflows around this SDK.
Borrowing it
Nothing to install: this file belongs to a2aproject/a2a-python. 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-python/main/AGENTS.mdgit clone --depth 1 https://github.com/a2aproject/a2a-pythonWrote 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/instructions/a2aproject/a2a-python/agents-md)<a href="https://agentmods.dev/instructions/a2aproject/a2a-python/agents-md"><img src="https://agentmods.dev/badge/instructions/a2aproject/a2a-python/agents-md/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/instructions/a2aproject/a2a-python/agents-md"><img src="https://agentmods.dev/badge/instructions/a2aproject/a2a-python/agents-md.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 | $0.00448 | $0.00448 |
| Opus 5.5 | $0.00179 | $0.00179 |
| Sonnet 5.5 | $0.00090 | $0.00090 |
| Haiku 4.5 | $0.00045 | $0.00045 |
Grade A, and why
a2a-python AGENTS.md 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 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.
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.
What it actually says
AGENTS.md
Python SDK for the Agent2Agent (A2A) Protocol
(a2a module, a2a-sdk distribution). It handles complex messaging, task management,
and communication across different transports (REST, gRPC, JSON-RPC).
Technology Stack & Architecture
- Language: Python 3.10+
- Package Manager:
uv - Lead Transports: Starlette (REST/JSON-RPC), gRPC
- Data Layer: SQLAlchemy (SQL), Pydantic (Logic/Legacy), Protobuf (Modern Messaging)
- Key Directories:
/src: Core implementation logic./tests: Comprehensive test suite./docs: AI guides and migration documentation.
Mandatory workflow
You MUST do all of the following:
-
At the start of every task that touches files, read
docs/ai/coding_conventions.md,docs/ai/mandatory_checks.md, anddocs/ai/evidence_rules.md. -
Before declaring any task done, run the full check sequence in
docs/ai/mandatory_checks.md— including for markdown/comment/whitespace-only changes. -
On any mistake, load the
mistake-reflectionskill at.agents/skills/mistake-reflection/SKILL.mdbefore continuing your response. The skill appends a structured entry todocs/ai/ai_learnings.md(gitignored local journal) so the user can use those findings to improve the workflow.When unsure: load the skill. False positives are free; false negatives are how the same mistake recurs.
Optional extras
pyproject.toml defines extras (grpc, telemetry, postgresql,
etc.). The dev group installs a2a-sdk[all], so anything gated behind
an extra must still import lazily at runtime — the install-smoke
harness verifies this per profile.
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 · 45 lines · 448 tokens per session scan A 5bbaddd1c852
a2a-python AGENTS.md is an instructions file published in the GitHub repository a2aproject/a2a-python (2,232 stars, last pushed yesterday), licensed Apache-2.0. It adds 448 tokens to every session, about $0.0018 per session on Opus 5.5. 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.
a2a-python AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| a2a-python AGENTS.mda2aproject/a2a-python | Instructions file | 2.2k | yesterday | Apache-2.0 | A | 448 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |