Borrowing it
Nothing to install: this file belongs to arcprime-ip/patent-prompts. 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/arcprime-ip/patent-prompts/main/AGENTS.mdgit clone --depth 1 https://github.com/arcprime-ip/patent-promptsWrote 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/arcprime-ip/patent-prompts/agents-md)<a href="https://agentmods.dev/instructions/arcprime-ip/patent-prompts/agents-md"><img src="https://agentmods.dev/badge/instructions/arcprime-ip/patent-prompts/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/arcprime-ip/patent-prompts/agents-md"><img src="https://agentmods.dev/badge/instructions/arcprime-ip/patent-prompts/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 | $0.00572 | $0.00572 |
| Opus 5 | $0.00286 | $0.00286 |
| Sonnet 5 | $0.00114 | $0.00114 |
| Haiku 4.5 | $0.00057 | $0.00057 |
Grade A, and why
patent-prompts 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 9d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Patent Prompts — Agent Instructions
This repository contains professional patent workflow prompts for AI coding agents. These prompts are designed by a patent attorney for real-world patent work including claims drafting, prosecution, prior art analysis, claim charting, continuation strategy, and portfolio management.
Repository Structure
pre-filing/ — Prompts for before filing a patent application
claims-drafting/ Draft claims from an invention disclosure
detectability-assessment/ Assess infringement detectability
disclosure-questions/ Generate clarifying questions for a disclosure
draft-review/ Review a draft for 101 and 112 issues (3 variants)
prior-art-analysis/ Analyze claims against prior art
prosecution/ — Prompts for patent prosecution
patent-summarization/ Summarize a patent from its claims
concept-extraction/ Extract key technical concepts from claims
portfolio/ — Prompts for portfolio management
continuation-targeted/ Draft continuation claims targeting a product
continuation-broadened/ Generate broader continuation claims
continuation-unclaimed/ Find disclosed but unclaimed subject matter
claim-chart/ Map claims to product features
categorization/ Categorize patents by technology area
pruning-analysis/ Evaluate maintain vs. abandon decisions
examples/ — Sample data and pre-filled example prompts
skills/ — SKILL.md files for Claude Code / agent skill installation
How to Use These Prompts
Each prompt lives in a prompt.md file within its category directory. The prompts use {{PLACEHOLDER}} format for user inputs (e.g., {{PATENT_CLAIMS}}, {{INVENTION_DESCRIPTION}}).
To use a prompt:
- Read the relevant
prompt.mdfile - Extract the prompt section between the
---delimiters - Replace all
{{PLACEHOLDER}}values with the user's content - Execute the completed prompt
Each prompt.md file contains a Placeholders table documenting what each placeholder expects.
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.
- 9d ago First seen · 53 lines · 572 tokens per session scan A a016fce3c241
patent-prompts AGENTS.md is an instructions file published in the GitHub repository arcprime-ip/patent-prompts (20 stars, last pushed 5mo ago), licensed MIT. It adds 572 tokens to every session, about $0.0029 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 2026-08-30.
Other instructions, from other repositories
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.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
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).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
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.