Borrowing it
Nothing to install: this file belongs to tenstorrent/tt-studio. 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/tenstorrent/tt-studio/main/CLAUDE.mdgit clone --depth 1 https://github.com/tenstorrent/tt-studioWrote 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/tenstorrent/tt-studio/claude-md)<a href="https://agentmods.dev/instructions/tenstorrent/tt-studio/claude-md"><img src="https://agentmods.dev/badge/instructions/tenstorrent/tt-studio/claude-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 | $0.01571 | $0.01571 |
| Opus 5 | $0.00785 | $0.00785 |
| Sonnet 5 | $0.00314 | $0.00314 |
| Haiku 4.5 | $0.00157 | $0.00157 |
Grade A, and why
tt-studio CLAUDE.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 8d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TT-Studio
Web interface for running AI models on Tenstorrent hardware. It wraps TT
Inference Server's packaging, containerization, and deployment automation around
TT-Metal model execution. Full deployment needs a Tenstorrent accelerator
(/dev/tenstorrent), but the frontend can also run against remote/cloud
inference endpoints with no local hardware.
Use
python run.pyfor everything —startup.shis deprecated. There are no git submodules;run.pyfetches the tt-inference-server artifact.
Architecture & ports
| Service | Port | Runtime | What it is |
|---|---|---|---|
| Frontend | 3000 | Docker (Nginx in prod) | React 18 + TypeScript + Vite + Tailwind |
| Backend | 8000 | Docker | Django REST API via uvicorn (ASGI + Channels/WebSocket) |
| Inference server | 8001 | Host | FastAPI wrapper over tt-inference-server (inference-api/) |
| Agent | 8080 | Docker | LLM agent service (app/agent/) |
| ChromaDB | 8111 | Docker | Vector DB for RAG |
| Docker control | 8002 | Host | JWT-secured Docker API wrapper (docker-control-service/) |
Containers share the tt_studio_network bridge; the backend reaches host
services via host.docker.internal. Health checks: backend GET /up/ and
GET /models/health/, inference server GET /health, frontend GET /.
Repo layout
app/backend/— Django project. Apps:api(settings, ASGI/WSGI, URL routing),docker_control(image pulls, container deploy, model execution),model_control(model registry, inference, TTS),board_control(hardware detection / telemetry),vector_db_control(Chroma RAG),logs_control,wakeword_control(voice activation, WebSocket consumers),shared_config(model/device config, model sync). Routes inapp/backend/api/urls.py.app/frontend/— React/TS/Vite app. Source undersrc/:components/,pages/,providers/,contexts/,hooks/,routes/,api/,lib/,types/. Backend proxy config invite.config.ts.app/agent/— agent service.inference-api/— FastAPI inference server.docker-control-service/— standalone Docker control service.models/— model definitions/config.dev-tools/— license/header tooling.dev-docs/— developer docs..cursor/rules/— editor rules..claude/skills/— assistant skills.
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.
- 8d ago First seen · 107 lines · 1,571 tokens per session scan A fce49e73cc78
tt-studio CLAUDE.md is an instructions file published in the GitHub repository tenstorrent/tt-studio (50 stars, last pushed today), licensed Apache-2.0. It adds 1,571 tokens to every session, about $0.0079 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.
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