Borrowing it
Nothing to install: this file belongs to ptonlix/beeweave. 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/ptonlix/beeweave/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/ptonlix/beeweaveWrote 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/ptonlix/beeweave/copilot-instructions)<a href="https://agentmods.dev/instructions/ptonlix/beeweave/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/ptonlix/beeweave/copilot-instructions/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/ptonlix/beeweave/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/ptonlix/beeweave/copilot-instructions.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 | $0.01354 | $0.01354 |
| Opus 5.5 | $0.00542 | $0.00542 |
| Sonnet 5.5 | $0.00271 | $0.00271 |
| Haiku 4.5 | $0.00135 | $0.00135 |
Grade A, and why
beeweave 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 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BeeWeave — Copilot Context
BeeWeave is an agent-native creation workbench for building a creative data flywheel: collect source material, create with agents, distill durable knowledge, reuse that knowledge as context, then collect better material for the next loop.
This repository contains the Python CLI, bundled skills, bootstrap templates, browser extension assets, tests, and documentation used to install and maintain BeeWeave workspaces.
Project Overview
- Purpose: Help agents and humans move material through a structured loop:
collect -> create -> distill -> reuse context -> collect better. - Runtime model:
workbench/is the staging and drafting area;vault/is the compiled markdown knowledge base. - CLI: The public console command is
bwe. - Package: Python package code lives under
beeweave/; package metadata and the CLI entrypoint live inpyproject.toml. - Skills: Source skills live under
.skills/wiki/and.skills/workbench/. Each skill folder uses aSKILL.mdworkflow file. - Bootstrap: Agent-facing setup templates live under
bootstrap/. - Extension: Browser capture assets live under
extensions/brain-capture/.
Key Concepts
- BeeWeave is a loop, not a one-way archive.
- Raw inputs, drafts, captures, web clips, and source libraries belong in
workbench/. - Stable reusable knowledge belongs in
vault/as markdown with metadata and Obsidian-style[[wikilinks]]. - The vault is a compiled artifact: concepts, entities, references, project notes, synthesis pages, and graph-ready relationships distilled from higher signal material.
- Setup-generated runtime
vault/andworkbench/directories should not be committed to this repository.
Runtime Layout
BeeWeave setup creates this structure inside a user-selected workspace:
project/
+-- vault/ # durable markdown knowledge
| +-- concepts/
| +-- entities/
| +-- skills/
| +-- references/
| +-- synthesis/
| +-- projects/
| +-- _meta/
| +-- _archives/
| +-- _staging/
| +-- .obsidian/
+-- workbench/ # staging and drafting area
+-- inbox/
| +-- captures/
| +-- web/
| +-- archived/
| +-- rejected/
+-- articles/
| +-- drafts/
| +-- published/
+-- library/
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 · 163 lines · 1,354 tokens per session scan A dbb204a9a49a
beeweave copilot-instructions.md is an instructions file published in the GitHub repository ptonlix/beeweave (6 stars, last pushed 2mo ago), licensed MIT. It adds 1,354 tokens to every session, about $0.0054 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.
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AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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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.
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).
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.