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/skills/mistake-reflection/SKILL.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/skills/a2aproject/a2a-python/mistake-reflection)<a href="https://agentmods.dev/skills/a2aproject/a2a-python/mistake-reflection"><img src="https://agentmods.dev/badge/skills/a2aproject/a2a-python/mistake-reflection/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-python/mistake-reflection"><img src="https://agentmods.dev/badge/skills/a2aproject/a2a-python/mistake-reflection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00060 | $0.01209 |
| Opus 5.5 | $0.00024 | $0.00484 |
| Sonnet 5.5 | $0.00012 | $0.00242 |
| Haiku 4.5 | $0.00006 | $0.00121 |
Grade A, and why
mistake-reflection 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.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mistake Reflection
Implements the mistake-handling step of AGENTS.md §"Mandatory
workflow".
When to load this skill
Trigger on ANY of these, without waiting for the user to ask:
- The user corrects a factual claim, code change, or assumption.
- A tool result contradicts something you just stated or did (lint failure, test failure, type-check failure, file not found, command exit non-zero on something you said would succeed).
- You re-read a file or doc and realize a prior statement was wrong or unverified.
- You realize mid-task that you skipped a required step
(e.g. didn't read
docs/ai/coding_conventions.md,docs/ai/mandatory_checks.md, ordocs/ai/evidence_rules.mdat task start). - You stated an inference as a fact without a
file:linecitation and later had to walk it back.
If unsure whether something counts: it counts. False positives are cheap; false negatives are how the same mistake recurs.
Procedure
Do these in order. Do NOT defer to the end of the task.
- Acknowledge the mistake to the user explicitly in the current response. One or two sentences. No hedging, no minimization.
- Read recent entries in
docs/ai/ai_learnings.md(at minimum the last 5 entries, or the whole file if shorter). If the current mistake is a recurrence of an existing rule, say so explicitly and reference the prior entry's date — do not silently duplicate. - Append a new entry to
docs/ai/ai_learnings.mdusing the template below. Append; do not rewrite existing entries. - Continue the original task only after steps 1–3 are done.
Entry template
Copy this verbatim, fill in each field, append to the end of the file
(after the existing --- separator):
## YYYY-MM-DD — <one-line summary>
- **Mistake**: What went wrong. Be concrete. Quote the wrong claim or
describe the wrong action. Include `file:line` references where
applicable.
- **Trigger**: How the mistake surfaced (user correction, tool output,
self-review). Include the specific signal if it was a tool result.
- **Root cause**: Why it happened. Distinguish between (a) missing
knowledge, (b) skipped verification step, (c) false assumption from
pattern-matching, (d) workflow gap. Avoid generic "I didn't think
carefully" — name the specific failure mode.
- **Recurrence of**: If this matches an existing rule, link to the
prior entry's date. Otherwise write "new".
- **Rule**: A concrete, checkable rule that would have prevented this.
Phrase as an imperative ("Before X, do Y"). If the rule already
exists and was violated, the rule should be about *enforcement*
(e.g. a check to add to a skill, a step to add to AGENTS.md), not a
restatement of the existing rule.
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 · 111 lines · 60 tokens per session scan A 22e4f978515b
mistake-reflection is a skill published in the GitHub repository a2aproject/a2a-python (2,232 stars, last pushed yesterday), licensed Apache-2.0. It adds 60 tokens to every session and 1,209 once invoked, about $0.0002 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.
mistake-reflection compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| mistake-reflectiona2aproject/a2a-python | Skill | 2.2k | yesterday | Apache-2.0 | A | 60 | Claude Code, Codex |
| frankfurtera2aproject/a2a-samples | Skill | 1.8k | 17d ago | Apache-2.0 | A | 14 | Claude Code, Codex |
| potpie-graphpotpie-ai/potpie | Skill | 5.8k | 7d ago | Apache-2.0 | A | 107 | Codex |
| potpie-repo-baselinepotpie-ai/potpie | Skill | 5.8k | 7d ago | Apache-2.0 | A | 75 | Claude Code, Codex |
| potpie-debug-memorypotpie-ai/potpie | Skill | 5.8k | 7d ago | Apache-2.0 | A | 41 | Claude Code, Codex |
| lucid-agentsdaydreamsai/lucid-agents | Skill | 201 | 3mo ago | MIT | A | 75 | Codex |
| session-logstrpc-group/trpc-agent-go | Skill | 1.9k | yesterday | Apache-2.0 | A | 20 | Claude Code, Codex |