K-Dense BYOK is a desktop AI research assistant that lets scientists describe research tasks in plain language and have an agent inspect data, run analysis code, search sources, and produce figures or reports. It is intended for scientific work across fields, using the user’s selected hosted or local AI models. The catalogue add-ons support its research workflow.
Borrowing it
Nothing to install: this file belongs to K-Dense-AI/k-dense-byok. 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/K-Dense-AI/k-dense-byok/main/AGENTS.mdgit clone --depth 1 https://github.com/K-Dense-AI/k-dense-byokWrote 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/k-dense-ai/k-dense-byok/agents-md)<a href="https://agentmods.dev/instructions/k-dense-ai/k-dense-byok/agents-md"><img src="https://agentmods.dev/badge/instructions/k-dense-ai/k-dense-byok/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/k-dense-ai/k-dense-byok/agents-md"><img src="https://agentmods.dev/badge/instructions/k-dense-ai/k-dense-byok/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 | $0.09412 | $0.09412 |
| Opus 5 | $0.04706 | $0.04706 |
| Sonnet 5 | $0.01882 | $0.01882 |
| Haiku 4.5 | $0.00941 | $0.00941 |
Grade A, and why
k-dense-byok 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 yesterday.
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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project overview
K-Dense BYOK is a local AI research-assistant app ("Kady") that brings the user's own model credentials (API keys or supported subscriptions). It runs natively on macOS, Linux, and Windows. It is one repo with two runtime services started together by the cross-platform launcher start.mjs (wrapped by ./start.sh on macOS/Linux and start.cmd on Windows):
| Service | Port | Code |
|---|---|---|
| Frontend (Next.js 16 / React 19) | 3000 | web/ |
| Backend (TypeScript + Pi coding-agent SDK) | 8000 | server/ |
The backend embeds the Pi SDK (@earendil-works/pi-coding-agent) and runs a single flat agent with built-in tools (read/bash/edit/write/grep/find/ls), a subagent/subagent_wait delegation pair (the pi-subagents extension package), an interview clarifying-questions tool (a native re-implementation of pi-interview — see server/src/agent/interview.ts; the form renders inline in the chat UI instead of the package's own browser window), the pi-web-access web tools (web_search/fetch_content/get_search_content; code_search was removed upstream — web_search's Exa provider covers it), live PDF annotation tools (add_pdf_annotation/list_pdf_annotations/remove_pdf_annotation), a hybrid durable Modal tool family (modal_run/modal_submit/modal_status/modal_wait/modal_cancel/modal_results/modal_submit_batch; server/src/agent/modal-tool.ts), and per-project MCP tools (.pi/mcp.json). PDF annotations and Modal jobs are also available to child agents through the vendored kady-pdf-annotations and kady-modal Pi packages; annotation sidecars use a shared cross-process lock and atomic replacement. Modal jobs are server-owned and restart-recoverable. There is no orchestrator/expert split, no Gemini CLI, and no LiteLLM proxy (all removed in the Pi migration). Models go directly to OpenRouter, connected Pi OAuth providers (openai-codex, anthropic, github-copilot, xai), NVIDIA NIM (API key), or local Ollama. Everything runs locally; user data lives in projects/.
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.
- yesterday Changed · +2 lines · +1,598 tokens per session 3a7c5b98a656
- 3d ago Changed · +347 tokens per session f1f42a65581c
- 9d ago First seen · 111 lines · 7,467 tokens per session scan A e92e58bf1be2
k-dense-byok AGENTS.md is an instructions file published in the GitHub repository K-Dense-AI/k-dense-byok (1,177 stars, last pushed yesterday), licensed MIT. It adds 9,412 tokens to every session, about $0.0471 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.