Dograh is an open-source, self-hostable platform for building voice AI agents that combine speech recognition, language models, and speech synthesis. Teams use its visual workflow builder and telephony integrations to create and operate voice agents while choosing their own providers and infrastructure.
Borrowing it
Nothing to install: this file belongs to dograh-hq/dograh. 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/dograh-hq/dograh/main/AGENTS.mdgit clone --depth 1 https://github.com/dograh-hq/dograhWrote 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/dograh-hq/dograh/agents-md)<a href="https://agentmods.dev/instructions/dograh-hq/dograh/agents-md"><img src="https://agentmods.dev/badge/instructions/dograh-hq/dograh/agents-md.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 5.1 | $0.00390 | $0.00390 |
| Opus 5 | $0.00195 | $0.00195 |
| Sonnet 5 | $0.00078 | $0.00078 |
| Haiku 4.5 | $0.00039 | $0.00039 |
Grade A, and why
dograh 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 6d 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
Dograh - Project Overview
Dograh is a voice AI platform for building and deploying conversational AI agents with telephony and WebRTC support.
Project Structure
dograh/
├── api/ # Backend - FastAPI application
├── ui/ # Frontend - Next.js application
├── scripts/ # Helper scripts for local development
├── docs/ # Mintlify documentation
├── pipecat/ # Pipecat framework (git submodule)
├── docker-compose.yaml # Production/OSS deployment
├── docker-compose-local.yaml # Local development services
Tech Stack
- Backend: Python with FastAPI
- Frontend: Next.js 15 with React 19, TypeScript, Tailwind CSS
- Database: PostgreSQL with SQLAlchemy (async)
- Cache/Queue: Redis with ARQ for background tasks
- Storage: MinIO (S3-compatible) for audio files
Local Development
Contributor setup and service startup are documented in docs/contribution/setup.mdx.
Environment Configuration
api/.env- Backend environment variables. Source this when running repo-owned backend scripts against the dev DB (e.g.python -m scripts.dump_docs_openapi).api/.env.test- Test-only environment variables. Source this when running pytest so tests hit the test DB and never the dev/prod credentials inapi/.env.ui/.env- Frontend environment variables
Typical invocation:
# Tests
source venv/bin/activate && set -a && source api/.env.test && set +a && python -m pytest api/tests/...
# Backend scripts
source venv/bin/activate && set -a && source api/.env && set +a && python -m scripts.dump_docs_openapi
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.
- 6d ago First seen · 45 lines · 390 tokens per session scan A 8d2faa49074b
dograh AGENTS.md is an instructions file published in the GitHub repository dograh-hq/dograh (5,589 stars, last pushed yesterday), licensed BSD-2-Clause. It adds 390 tokens to every session, about $0.0019 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
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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.
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.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.