Borrowing it
Nothing to install: this file belongs to shigella520/MindTrain. 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/shigella520/MindTrain/main/AGENTS.mdgit clone --depth 1 https://github.com/shigella520/MindTrainWrote 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/shigella520/mindtrain/agents-md)<a href="https://agentmods.dev/instructions/shigella520/mindtrain/agents-md"><img src="https://agentmods.dev/badge/instructions/shigella520/mindtrain/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/shigella520/mindtrain/agents-md"><img src="https://agentmods.dev/badge/instructions/shigella520/mindtrain/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 | $0.00559 | $0.00559 |
| Opus 5.5 | $0.00224 | $0.00224 |
| Sonnet 5.5 | $0.00112 | $0.00112 |
| Haiku 4.5 | $0.00056 | $0.00056 |
Grade A, and why
MindTrain 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.
How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Instructions
MindTrain target architecture
- Treat MindTrain as a domain-independent knowledge-training platform, not as a Java-only Skill.
- Use
doc/目标需求.mdas the product requirements source anddoc/概要设计.mdas the architecture source. - Keep Training Core as the source of truth for questions, candidates, prompts, sessions, attempts, review events, scheduler bindings, and plugin sync state.
- Keep Codex Skills stateless: they orchestrate MCP/API tools and must not become the authoritative application database.
- Keep scheduler behavior behind a provider contract. The initial providers are Core 加权调度 (stable ID:
weighted) and the optional Anki scheduler plugin. - Treat Anki as a scheduling plugin and rebuildable local projection, not as the authoritative MindTrain question bank.
- Keep production runtime data out of the repository; retain only migrations, contracts, deployment configuration, and minimal non-private test fixtures.
- Do not introduce microservices prematurely. Build Training Core as a modular monolith first.
Training and content integrity
- Use
plugins/mindtrain/skills/mindtrain/SKILL.mdas the only MindTrain Skill source. - Access questions, candidates, sessions, attempts, mastery and reports only through Trainer MCP or Training Core APIs.
- Permit an unanswered generated candidate only in its owning session; answering activates it, while explicit rejection physically deletes it.
- Grade single- and multiple-choice answers by exact option-set equality; scores are only 100 or 0.
- Never show an example answer combination that could disclose the correct answer count or option set. Use neutral text such as
请回复选项字母，可用逗号分隔. - Record source URL, access date, version, and review state for generated questions.
- Increment the version when published question content or scoring criteria change.
- Use test-local fixtures rather than repository question banks or personal learning files.
Safety and integrity
- Do not commit secrets, API keys, Anki credentials, access tokens, or private learning material.
- Do not overwrite or delete existing user learning data while restructuring the platform.
- Make external integrations idempotent and retain enough state to recover partial Core/plugin failures.
- Keep third-party MCP and Anki Add-on APIs behind MindTrain-owned adapters.
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 · 38 lines · 559 tokens per session scan A 5176592ebeeb
MindTrain AGENTS.md is an instructions file published in the GitHub repository shigella520/MindTrain (128 stars, last pushed 22d ago), licensed MIT. It adds 559 tokens to every session, about $0.0022 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.
MindTrain AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| MindTrain AGENTS.mdshigella520/MindTrain | Instructions file | 128 | 22d ago | MIT | A | 559 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |