Borrowing it
Nothing to install: this file belongs to prantikmedhi/lore. 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/prantikmedhi/lore/main/AGENTS.mdgit clone --depth 1 https://github.com/prantikmedhi/loreWrote 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/prantikmedhi/lore/agents-md)<a href="https://agentmods.dev/instructions/prantikmedhi/lore/agents-md"><img src="https://agentmods.dev/badge/instructions/prantikmedhi/lore/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/prantikmedhi/lore/agents-md"><img src="https://agentmods.dev/badge/instructions/prantikmedhi/lore/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 | $0.00479 | $0.00479 |
| Opus 5.5 | $0.00192 | $0.00192 |
| Sonnet 5.5 | $0.00096 | $0.00096 |
| Haiku 4.5 | $0.00048 | $0.00048 |
Grade A, and why
lore 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 1mo 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lore Agent Guide
Target locale: en.
This repository provides a complete NotebookLM automation layer for AI assistants. Agents should use source-grounded workflows, preserve citations, and create requested artifacts with the local scripts.
Repository Surfaces
| Surface | Location | Purpose |
|---|---|---|
| CLI | scripts/ |
Notebook operations, pipeline planning, artifact builders. |
| MCP | mcp_server/ |
Tool helpers for MCP-compatible clients. |
| Skill | SKILL.md |
Agent behavior and workflow rules. |
| Docs | docs/ and references/ |
Setup, clients, API surface, output formats, recipes. |
Agent Rules
- Target locale:
en. - Do not add personal credits or attribution blocks.
- Prefer source-grounded NotebookLM answers.
- Preserve citations, URLs, titles, dates, and uncertainty.
- Use JSON plans when automation is needed.
- Use Markdown for human-facing reports.
- Create artifacts when user requests outputs, not only plans.
Powered Mode Workflow
- Classify sources with
lore-source-manifestorlore manifest. - Create or reuse notebook.
- Add all relevant sources.
- Ask focused research questions.
- Synthesize cited answer.
- Generate requested artifacts.
- Index outputs with
lore-export-bundle.
Common Commands
lore list
lore create --title "Research" --sources https://example.com
lore ask --notebook "Research" --query "What are the key findings?"
lore-pipeline generate-all --title "Research" --sources https://example.com --output output/plan.json
lore-report --input output/plan.json --output output/report.md
lore-ppt --input output/report.md --output output/deck.pptx
lore-study-pack --input output/report.md --output-dir output/study-pack
lore-export-bundle --artifact-dir output --output output/bundle.json
Expected Artifacts
- Structured research brief
- Cited answer
- Markdown report
- PPTX slide deck
- Podcast script
- Video plan
- Flashcards
- Quiz
- Mind map
- Architecture summary
- Code explanation
- Study pack
- Bundle index
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.
- 1mo ago First seen · 64 lines · 479 tokens per session scan A eb0a0d385701
lore AGENTS.md is an instructions file published in the GitHub repository prantikmedhi/lore (2 stars, last pushed 3mo ago), licensed MIT. It adds 479 tokens to every session, about $0.0019 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 2026-08-31.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).