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tt-studio: Skill for Claude Code

.claude/skills/tt-studio-overview/SKILL.md

tt-studio-overview is a skill for Claude Code from tenstorrent/tt-studio. It costs 85 tokens per session (668 once invoked), scanned A, original, Apache-2.0.

A project overview for TT-Studio, a web interface for running AI models on Tenstorrent hardware through a React frontend, Django backend, FastAPI server, and Docker.

In plain words
What is it for?
Use it to orient yourself in the repository, locate setup or troubleshooting documentation, and understand how the frontend, backend, inference server, and hardware fit together.
Why use it?
It gives an unfamiliar developer a map of the platform, its main components, supported model uses, and where to find relevant documentation.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is tenstorrent/tt-studio's own configuration. It tells Claude Code how to work on tt-studio itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything tt-studio configures →

not rated 52repo yesterday A scan SkillSpector: pass 85 tokens original Apache-2.0
View source ↗ tenstorrent/tt-studio docs.tenstorrent.com
Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/tenstorrent/tt-studio/main/.claude/skills/tt-studio-overview/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/tenstorrent/tt-studio

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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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.

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Your own site · 80×15
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Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 668 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00085 $0.00668
Opus 5.5 $0.00034 $0.00267
Sonnet 5.5 $0.00017 $0.00134
Haiku 4.5 $0.00009 $0.00067

Measured 2mo ago against content hash d1810de977b8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

tt-studio-overview 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 2mo 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.

.claude/skills/tt-studio-overview/SKILL.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TT-Studio

TT-Studio is an easy-to-use web interface for running AI models on Tenstorrent hardware. It combines TT Inference Server's core packaging setup, containerization, and deployment automation with TT-Metal's model execution framework specifically optimized for Tenstorrent hardware.

Important notes:

  • TT-Studio requires access to a Tenstorrent AI accelerator for full deployment features
  • Alternatively, you can connect just the frontend to a remote API endpoint without direct hardware access
  • The platform provides automatic hardware detection and seamless integration with Tenstorrent devices
  • Uses containerized deployment through Docker for isolation and easy deployment
  • The startup.sh script is deprecated - use python run.py for all operations

Docs

Examples

Key Components

  • Frontend Interface: Modern React-based UI for model interaction and management
  • Backend API: Django-based service for model management, deployment, and API endpoints
  • TT Inference Server: FastAPI server for handling model inference requests
  • Docker Containers: Complete containerization for isolation and easy deployment
  • Automatic Hardware Detection: Seamless integration and auto-mounting of Tenstorrent devices (/dev/tenstorrent)
  • Automated Setup: Complete environment configuration and model setup automation via run.py script

Read the full file on GitHub · 56 lines

Changes

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.

  1. 2mo ago First seen · 56 lines · 85 tokens per session scan A d1810de977b8

Subscribe to this mod's changes

tt-studio-overview is a skill published in the GitHub repository tenstorrent/tt-studio (52 stars, last pushed yesterday), licensed Apache-2.0. It adds 85 tokens to every session and 668 once invoked, about $0.0003 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 2026-08-30.

Backend and APIsDevOps and cloudFrontendReactacceleratorai-agentsbackend-servicechat-applicationui-components
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