Borrowing it
Nothing to install: this file belongs to pjwang2022/Monstrare. 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/pjwang2022/Monstrare/main/AGENTS.mdgit clone --depth 1 https://github.com/pjwang2022/MonstrareWrote 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/pjwang2022/monstrare/agents-md)<a href="https://agentmods.dev/instructions/pjwang2022/monstrare/agents-md"><img src="https://agentmods.dev/badge/instructions/pjwang2022/monstrare/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/pjwang2022/monstrare/agents-md"><img src="https://agentmods.dev/badge/instructions/pjwang2022/monstrare/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 | $0.00848 | $0.00848 |
| Opus 5.5 | $0.00339 | $0.00339 |
| Sonnet 5.5 | $0.00170 | $0.00170 |
| Haiku 4.5 | $0.00085 | $0.00085 |
Grade A, and why
Monstrare 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
Agent 指令
本專案使用 Monstrare。請遵循
ai/process/workflow.md 中的共用流程。
操作規則
- 不得根據模糊的需求實作非小型（non-trivial）變更。
- 從情境探索（context discovery）與任務專屬的情境包（context pack）開始。
- 實作前使用
ai/process/definition-of-ready.md。 - 宣告完成前使用
ai/process/definition-of-done.md。 - UI 變更需要畫面規格與 mockup 決策紀錄（以
ai/templates/screen-spec.md、ai/templates/mockup-decision.md為範本，產出到ai/artifacts/<Epic>/），並先對照ai/context/design-system.md：重用既有 design token 與元件，缺的元件照既有風格補做並登記回元件庫 inventory。 - 範本（
ai/templates/）唯讀；所有填寫完成的產出物依ai/artifacts/README.md的慣例存放。 - 任何 mockup 或前端視覺實作，套用
ai/skills/design-craft.md的設計工藝紀律，交付前對照ai/checklists/design-review-checklist.md。 - Epic 0 的 UI 設計系統須依五階段（框架 → 風格 → design token → 元件庫 → 版面）分關卡展開，不得一步到位直接畫版面（見
ai/skills/project-kickoff.md步驟 2a）。 - 高風險變更需要架構、安全性與測試審查關卡（review gate）。
- 優先採用既有專案模式，而非新增抽象層。
- 將變更範圍限制在已核准的任務卡（task card）內。
- 不得在未告知的情況下變更不相關的檔案。
- 提供驗證證據：指令、輸出結果、UI 的螢幕截圖，以及已知的殘留風險。
必要流程
若是全新專案、還沒有 Epic/User Story 待辦清單，先執行 project-kickoff 流程，
把專案拆解成 Epic → User Story → Task 並建立看板卡片，再對每張任務卡套用下方流程。
- 若
ai/context/project-map.md存在，先閱讀它。 - 若專案情境缺失或過時，執行 project-search 工作流程。
- 對於新功能，建立或更新功能規格書。
- 對於 UI 工作，產出多個 mockup 變體並等待人工選擇。
- 產出 AI-ready 的任務卡。
- 一次實作一張已核准的任務卡。
- 執行驗證。
- 執行審查關卡。
- 彙整證據並在需要時請求人工驗收。
審查準則
審查程式碼時，優先關注：
- 功能性錯誤與回歸問題。
- 安全性與隱私風險。
- 身分驗證（auth）、權限、密鑰（secret）、檔案、網路與金流邊界。
- 資料驗證與錯誤處理。
- 可維護性、重複程式碼與架構偏移（architectural drift）。
- 缺失的測試或薄弱的驗證。
發現的問題應盡可能包含檔案與行號參照。
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 · 49 lines · 848 tokens per session scan A 166fce558943
Monstrare AGENTS.md is an instructions file published in the GitHub repository pjwang2022/Monstrare (94 stars, last pushed 4mo ago), licensed MIT. It adds 848 tokens to every session, about $0.0034 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.
Monstrare AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| Monstrare AGENTS.mdpjwang2022/Monstrare | Instructions file | 94 | 4mo ago | MIT | A | 848 | 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 | today | 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 |