Agent skill · Backend & API

together-cost-tuning

Together AI cost tuning for inference, fine-tuning, and model deployment. Use when working with Together AI''s OpenAI-compatible API. '

jeremylongshoregithub.com/jeremylongshoreGitHub ↗
claude-codecan modify filesMIT
Install
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill together-cost-tuning --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 2 KB
Bundled scripts: none
Version: 1.6.0
Declared author: Jeremy Longshore <jeremy@intentsolutions.io>
Allowed tools: ReadWriteEditBash(pip:*)Grep
Requires: Designed for Claude Code
Path: plugins/saas-packs/together-pack/skills/together-cost-tuning/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,596
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Together AI Cost Tuning ## Overview Optimize Together AI costs with model selection, batching, and caching. ## Instructions ### Together AI Pricing Model | Model Category | Price (per 1M tokens) | Example Models | |---------------|----------------------|----------------| | Small (< 10B) | $0.10-0.30 | Llama-3.2-3B, Qwen-2.5-7B | | Medium (10-40B) | $0.60-1.20 | Mixtral-8x7B, Llama-3.3-70B-Turbo

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About this skill
What does the together-cost-tuning skill do?

Together AI cost tuning for inference, fine-tuning, and model deployment. Use when working with Together AI''s OpenAI-compatible API. '

How do I install it?

Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill together-cost-tuning --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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