Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/u9401066/hyperhierarchicalrag/copilot-instructionsgit clone --depth 1 https://github.com/u9401066/HyperHierarchicalRAGWrote 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/u9401066/hyperhierarchicalrag/copilot-instructions)<a href="https://agentmods.dev/instructions/u9401066/hyperhierarchicalrag/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/u9401066/hyperhierarchicalrag/copilot-instructions.svg" alt="Measured on agentmods" 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 | $0.00848 | $0.00848 |
| Opus 5 | $0.00424 | $0.00424 |
| Sonnet 5 | $0.00170 | $0.00170 |
| Haiku 4.5 | $0.00085 | $0.00085 |
Grade A, and why
HyperHierarchicalRAG copilot-instructions.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 3d 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
Copilot Instructions for Zotero + PubMed MCP
Auto-generated by Zotero + PubMed MCP Extension 此檔案由 Extension 自動創建,幫助 Copilot 更好地使用研究工具
可用的 MCP Servers
1. Zotero Keeper
管理 Zotero 書目庫的工具,包括:
- 文獻搜尋與瀏覽
- PubMed 文獻匯入
- Collection 管理
- 書庫分析
2. PubMed Search
搜尋醫學文獻的工具,包括:
- 文獻搜尋(支援 PICO 策略)
- 引用分析
- 全文連結取得
- Session 管理
核心工作流程
🔍 搜尋新文獻
- 使用
parse_pico分析研究問題 - 使用
generate_search_queries產生搜尋策略 - 使用
search_literature搜尋 PubMed - 結果自動快取,用
get_session_pmids取回
📥 匯入到 Zotero
重要: 匯入前必須詢問用戶要存入哪個 Collection!
- 使用
list_collections取得 Collection 列表 - 詢問用戶選擇 Collection
- 使用
quick_import_pmids或batch_import_from_pubmed匯入
🔄 避免重複
- 使用
check_articles_owned檢查 PMID 是否已存在 - 使用
search_pubmed_exclude_owned直接搜尋未擁有的文獻 - 使用
get_cached_article取得快取的文章(避免重複 API 呼叫)
回應風格
- 使用繁體中文
- 清楚說明每個步驟
- 匯入前確認用戶意圖
VS Code Copilot Agent 指引 (整合自 AGENTS.md)
此部分為 VS Code GitHub Copilot 的 Agent Mode 提供專案上下文。
專案規則
法規遵循
你必須遵守以下法規層級:
- 憲法:
CONSTITUTION.md- 最高原則,不可違反 - 子法:
.github/bylaws/*.md- 細則規範 - 技能:
.claude/skills/*/SKILL.md- 操作程序
架構與環境原則
- DDD 架構:DAL 必須獨立,依賴方向:
Presentation → Application → Domain ← Infrastructure。 - Python (uv 優先):優先使用
uv管理環境,禁止全域安裝。 - Memory Bank:重要操作後必須更新同步檔案(
progress.md,activeContext.md等)。 - Git 工作流:提交前執行檢查清單(同步記憶、更新 README/CHANGELOG 等)。
可用 Skills (.claude/skills/)
包含 git-precommit, ddd-architect, code-refactor, memory-updater, test-generator 等 13 個自動化開發技能。
💸 Memory Checkpoint 規則
為避免 Context 遺失,於以下時機執行「checkpoint」:
- 對話超過 10 輪
- 修改超過 5 個檔案
- 完成重要功能
- 使用者暫時離開
必記:當前焦點、變更列表、待辦事項、下一步計畫。
代理回應風格
- 使用繁體中文,提供清晰步驟說明。
- 引用相關法規條文,執行操作後更新 Memory Bank。
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.
- 3d ago First seen · 82 lines · 848 tokens per session scan A 12d9ca2cbfa1
HyperHierarchicalRAG copilot-instructions.md is an instructions file published in the GitHub repository u9401066/HyperHierarchicalRAG (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 848 tokens to every session, about $0.0042 per session on Opus 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 2026-08-31.
Other instructions, from other repositories
repo-graphrag-mcp AGENTS.md
Instructions for yumeiriowl/repo-graphrag-mcp, covering repo graphrag mcp usage guide, prerequisites, three tools, tool 1: graphcreate and tool 2: graphquery.
edgequake AGENTS.md
AGENTS.md instructions for raphaelmansuy/edgequake, covering repository guidelines, project structure & module organization, build, test, and development commands, quick start with make and start with ollama (default).
VelociRAG AGENTS.md
Instructions for HaseebKhalid1507/VelociRAG, covering agents.md — velocirag for ai coding agents, what is this?, architecture, module map and key classes.
myrmion-graphrag CLAUDE.md
Claude Code instructions for e2its/myrmion-graphrag, covering claude.md, qué es esto, herramientas del servidor myrmion-graphrag (documentos), herramientas del servidor myrmion-codebase (código) and mantenimiento obligatorio del codebaseinventory.
llm-wiki-agent GEMINI.md
Gemini CLI instructions for SamurAIGPT/llm-wiki-agent, covering llm wiki agent — schema & workflow instructions, how to use, directory layout, page format and ingest workflow.
remnic AGENTS.md
AGENTS.md instructions for joshuaswarren/remnic, covering remnic - agent guide, architecture boundaries (non-negotiable), upstream references, adapter implementation rules and openclaw compatibility window.