Borrowing it
Nothing to install: this file belongs to oyorf/person_dashboard. 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/oyorf/person_dashboard/main/AGENTS.mdgit clone --depth 1 https://github.com/oyorf/person_dashboardWrote 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/oyorf/person_dashboard/agents-md)<a href="https://agentmods.dev/instructions/oyorf/person_dashboard/agents-md"><img src="https://agentmods.dev/badge/instructions/oyorf/person_dashboard/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/oyorf/person_dashboard/agents-md"><img src="https://agentmods.dev/badge/instructions/oyorf/person_dashboard/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 | $0.00340 | $0.00340 |
| Opus 5.5 | $0.00136 | $0.00136 |
| Sonnet 5.5 | $0.00068 | $0.00068 |
| Haiku 4.5 | $0.00034 | $0.00034 |
Grade A, and why
person_dashboard 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
Personal AI Workbench public repository rules
This repository is the public, privacy-safe edition of Personal AI Workbench.
Public data boundary
- Never copy a real user's Vault, account export, comments, messages, browsing history, credentials, local paths, screenshots, or generated reports into this repository.
- Runtime examples live only under
个人知识库/and must be synthetic, clearly labelled demo data. wiki/demo content is limited to genericconceptsandframeworkspages. Do not add personal cases, diagnoses, analyses, source archives, or reading notes.- Douyin examples must use the documented schema with invented titles, ids, dates, and metrics. Never derive examples by lightly editing a real export.
- Local overrides belong in ignored files such as
Workbench/.envandWorkbench/config/attention.local.json.
Public feature boundary
- The public navigation does not expose Brainstorm, run archives, or WeChat Official Account modules.
- The default Vault is the repository-level
个人知识库/sibling ofWorkbench/. A user may point the app at another Vault throughPERSONAL_DASHBOARD_VAULT_ROOT. - Missing data remains missing. Demo values must always be labelled as synthetic in both files and UI.
- Keep the application loopback-only by default. Do not expose local mutation APIs to a LAN-facing host.
Release gate
Before publishing, run:
cd Workbench
npm test
npm run build
npm run privacy:scan
The privacy scan must reject personal usernames, home-directory paths, private Vault names, common credential assignments, and known private product identifiers.
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 · 32 lines · 340 tokens per session scan A db5230dda5c3
person_dashboard AGENTS.md is an instructions file published in the GitHub repository oyorf/person_dashboard (301 stars, last pushed 2mo ago), licensed MIT. It adds 340 tokens to every session, about $0.0014 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.
person_dashboard AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| person_dashboard AGENTS.mdoyorf/person_dashboard | Instructions file | 301 | 2mo ago | MIT | A | 340 | 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 | yesterday | 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 | 275k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |