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Agent skill

Together Core Workflow A

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Prepare, submit, monitor, and disposition a Together AI fine-tuning job using SDK v2, validated training data, explicit cost approval, and separate deployment verification.

MITAuto-check passedAI & LLM Engineering

Install Together Core Workflow A

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill together-core-workflow-a -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace together-core-workflow-a --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/together-core-workflow-a .claude/skills/together-core-workflow-a && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
together-core-workflow-a
GitHub stars
2.8k
Token cost
~1.1k tokens
SKILL.md length
406 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Prepare, submit, monitor, and disposition a Together AI fine-tuning job using SDK v2, validated training data, explicit cost approval, and separate deployment verification.

  • Works in 6 steps: Define the target behavior, baseline… → Validate format, licenses, consent,… → Confirm the base model is currently… → …
  • Adapting a model to custom examples
  • SKILL.md covers Overview, Prerequisites, Tool Discipline and Current Contract, plus 7 more sections
  • Needs TOGETHER_API_KEY

What it does

Together Core Workflow A is an agent skill from jeremylongshore/tons-of-skills-marketplace. Prepare, submit, monitor, and disposition a Together AI fine-tuning job using SDK v2, validated training data, explicit cost approval, and separate deployment verification. Use when adapting a model to custom examples or preferences. Trigger with "Together fine-tune", "train a Together model", or "Together DPO job".

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/official-docs.md`). Compatibility notes: Designed for Claude Code; submission requires network access, a project key, training data, and funded Together AI usage

It sits in AI & LLM Engineering, covering Fine-tuning and Deployment. It works with Together AI. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Adapting a model to custom examples
  • With Together fine-tune
  • Train a Together model
  • Together DPO job

Example prompts

  • “Together fine-tune”
  • “train a Together model”
  • “Together DPO job”
  • “/together-core-workflow-a”

Requirements

  • Python 3
  • A credential in TOGETHER_API_KEY
  • Compatibility (from SKILL.md): Designed for Claude Code; submission requires network access, a project key, training data, and funded Together AI usage
  • Pre-approved tools (allowed-tools): Read, Glob, Grep, WebFetch, Write, Edit

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Define the target behavior, baseline evaluation, tuning method, and success threshold.
  2. Validate format, licenses, consent, duplication, leakage, train/validation separation, and token distribution.
  3. Confirm the base model is currently tunable and estimate cost before upload.
  4. Upload with the fine-tune purpose and persist the returned file ID in a redacted manifest.
  5. Submit only after approval; persist job ID, parameters, dataset hash, owner, and cancellation threshold.
  6. Poll boundedly, review events/checkpoints, evaluate the output, and hand deployment off separately.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • WebFetch
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.together.ai
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • TOGETHER_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code; submission requires network access, a project key, training data, and funded Together AI usage

    From compatibility in the SKILL.md frontmatter.

Context cost

Together Core Workflow A loads about 1.1k tokens when it runs, and up to ~1.8k if it reads all its reference files. Until then it costs about 86 tokens; SKILL.md has 406 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~86
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 406 words, ~1,050 tokens.

Download SKILL.mdSave it as .claude/skills/together-core-workflow-a/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
together-core-workflow-a
description
Prepare, submit, monitor, and disposition a Together AI fine-tuning job using SDK v2, validated training data, explicit cost approval, and separate deployment verification. Use when adapting a model to custom examples or preferences. Trigger with "Together fine-tune", "train a Together model", or "Together DPO job".
allowed-tools
Read, Glob, Grep, WebFetch, Write, Edit
compatibility
Designed for Claude Code; submission requires network access, a project key, training data, and funded Together AI usage
argument-hint
[repository-path] [training-file] [sft|dpo]
version
1.9.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
saas, together-ai, fine-tuning
model
inherit
effort
high

Together AI Fine-Tuning Workflow

Overview

This skill governs the expensive path from dataset qualification through an asynchronous fine-tune job and a separately approved serving handoff.

Prerequisites

  • A supported base model and tuning method confirmed in current Together documentation
  • Sanitized, licensed training and optional validation JSONL
  • Dataset-quality and holdout criteria
  • A cost ceiling, job owner, cancellation rule, and deployment decision owner

Tool Discipline

Use Read, Glob, and Grep to inspect data schemas, training configuration, and existing evaluations. Use WebFetch for current supported models and job parameters. Use Write or Edit only for approved data-validation, job-manifest, or evaluation files; never copy raw sensitive data into the skill output.

Current Contract

  • Use Together Python SDK v2 and client.files.upload() plus client.fine_tuning.create().
  • The CLI accepts a file ID or local path and reports an estimated price before confirmation.
  • Prefer LoRA unless full tuning is justified; choose SFT or DPO from the behavior objective.
  • A completed training job does not automatically deploy a model. Serving is a separate endpoint decision.

Authentication

Fine-tuning APIs use the project-scoped TOGETHER_API_KEY Bearer credential. A W&B key, private Hugging Face token, or dataset-store credential is separate and must be scoped, stored, and redacted independently.

Instructions

  1. Define the target behavior, baseline evaluation, tuning method, and success threshold.
  2. Validate format, licenses, consent, duplication, leakage, train/validation separation, and token distribution.
  3. Confirm the base model is currently tunable and estimate cost before upload.
  4. Upload with the fine-tune purpose and persist the returned file ID in a redacted manifest.
  5. Submit only after approval; persist job ID, parameters, dataset hash, owner, and cancellation threshold.
  6. Poll boundedly, review events/checkpoints, evaluate the output, and hand deployment off separately.
Show full SKILL.md (131 more words)Show less

Approval Boundaries

Do not upload data or confirm a paid job without dataset authority and cost approval. Do not deploy the resulting model or delete training artifacts automatically.

Output

Return dataset checks, base model, method, estimated/approved cost, file and job references, terminal state, evaluation delta, and deployment recommendation.

Error Handling

ConditionResponse
Dataset validation failsStop before upload and report line-level categories without sensitive rows.
Base model unsupportedRe-resolve the fine-tuning catalog; do not substitute silently.
Job cost exceeds ceilingDo not confirm; reduce scope or seek approval.
Job fails or stallsCapture events, stop bounded polling, and preserve IDs for support.

Examples

The example below shows the minimum redacted evidence expected from a successful invocation of this operator workflow.

text
method=lora-sft; data=validated; estimate=approved; job=ft-redacted; deploy=not-started

Resources

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/together-core-workflow-a of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/official-docs.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Together Core Workflow A next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Together Core Workflow A compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Together Core Workflow A this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.1kAutomated safety check: PassMIT
Aqua CLIoracle/accelerated-data-science125—~2.1kAutomated safety check: PassUPL-1.0
Finetuningmicrosoft/GitHub-Copilot-for-Azure2551 repos~1.4kAutomated safety check: PassMIT
Agent Platform Eval Flywheelgoogle/skills21k—~7.4kAutomated safety check: PassApache-2.0
Quantized Exportwshobson/agents40k—~2kAutomated safety check: PassMIT
Kiln Check Finetune DeprecationKiln-AI/Kiln5.2k—~1.9kAutomated safety check: NotesCustom licence

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Works with

Categories

Questions about Together Core Workflow A

What does Together Core Workflow A do?

Prepare, submit, monitor, and disposition a Together AI fine-tuning job using SDK v2, validated training data, explicit cost approval, and separate deployment verification. Together Core Workflow A is an agent skill from jeremylongshore/tons-of-skills-marketplace. Prepare, submit, monitor, and disposition a Together AI fine-tuning job using SDK v2, validated training data, explicit cost approval, and separate deployment verification.

When should I use Together Core Workflow A?

Together Core Workflow A fits situations like: adapting a model to custom examples; with Together fine-tune; train a Together model; together DPO job.

How do I install Together Core Workflow A in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill together-core-workflow-a -a claude-code`. Or copy the skill folder (skills/.curated/together-core-workflow-a in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/together-core-workflow-a in your project. Claude Code loads it when a task matches its description.

How do I install Together Core Workflow A in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill together-core-workflow-a -a codex`. Or copy the skill folder (skills/.curated/together-core-workflow-a in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/together-core-workflow-a in your project. Codex loads it when a task matches its description.

Can I use Together Core Workflow A in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill together-core-workflow-a -a cursor` (or -a -a, -a or -a for the others). To copy it by hand, put the folder in .cursor/skills/together-core-workflow-a, .gemini/skills/together-core-workflow-a, .github/skills/together-core-workflow-a and .opencode/skills/together-core-workflow-a in your project.

What does Together Core Workflow A need to run?

Going by SKILL.md and its folder, Together Core Workflow A needs credentials named TOGETHER_API_KEY. Our summary lists: Python 3; A credential in TOGETHER_API_KEY. Its frontmatter pre-approves these tools: Read, Glob, Grep, WebFetch, Write, Edit. Compatibility (from SKILL.md): Designed for Claude Code; submission requires network access, a project key, training data, and funded Together AI usage.

Does Together Core Workflow A access the network?

SKILL.md names 2 domains. As links in the text: docs.together.ai and github.com. This is read from the text; nothing was executed.

Is Together Core Workflow A safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Together Core Workflow A use?

Together Core Workflow A is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Together Core Workflow A use?

About 1.1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 758 tokens, read only when the agent opens those files.

What are the alternatives to Together Core Workflow A?

Skills that share tags, products or a category with Together Core Workflow A: Aqua CLI (oracle/accelerated-data-science, 125 stars), Finetuning (microsoft/GitHub-Copilot-for-Azure, 255 stars), Agent Platform Eval Flywheel (google/skills, 21k stars) and Quantized Export (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Together Core Workflow A?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.