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Agent skill

Together Deploy Integration

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

Deploy and roll back Together AI integrations across serverless inference or v2 Dedicated Model Inference with secret injection, health probes, traffic control, and cost shutdown.

MITAuto-check passedBackend & APIs

Install Together Deploy Integration

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

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace together-deploy-integration --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-deploy-integration .claude/skills/together-deploy-integration && 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-deploy-integration
GitHub stars
2.8k
Token cost
~1.1k tokens
SKILL.md length
403 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Deploy and roll back Together AI integrations across serverless inference or v2 Dedicated Model Inference with secret injection, health probes, traffic control, and cost shutdown.

  • Works in 6 steps: Classify the workload as serverless or… → Pin the application artifact, SDK major,… → For dedicated v2, resolve model/config… → …
  • Releasing Together-backed services
  • SKILL.md covers Overview, Prerequisites, Tool Discipline and Current Contract, plus 7 more sections
  • Needs TOGETHER_API_KEY

What it does

Together Deploy Integration is an agent skill from jeremylongshore/tons-of-skills-marketplace. Deploy and roll back Together AI integrations across serverless inference or v2 Dedicated Model Inference with secret injection, health probes, traffic control, and cost shutdown. Use when releasing Together-backed services or dedicated models. Trigger with "deploy Together", "Together dedicated endpoint", or "Together rollout".

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; deployment requires platform access and Together AI project authorization

It sits in Backend & APIs, covering Deployment and Serverless. 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

  • Releasing Together-backed services
  • Dedicated models
  • With deploy Together
  • Together dedicated endpoint

Example prompts

  • “deploy Together”
  • “Together dedicated endpoint”
  • “Together rollout”
  • “/together-deploy-integration”

Requirements

  • A credential in TOGETHER_API_KEY
  • Compatibility (from SKILL.md): Designed for Claude Code; deployment requires platform access and Together AI project authorization
  • 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. Classify the workload as serverless or dedicated from latency, throughput, model, and utilization evidence.
  2. Pin the application artifact, SDK major, configuration schema, model policy, and secret references.
  3. For dedicated v2, resolve model/config resources, create the deployment, and poll to ready before routing traffic.
  4. Run a non-sensitive health probe that validates provider reachability and response shape.
  5. Shift a bounded canary while monitoring error rate, latency, usage, quality, and cost.
  6. Promote or roll back explicitly; scale obsolete dedicated replicas to zero and verify billing disposition.

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; deployment requires platform access and Together AI project authorization

    From compatibility in the SKILL.md frontmatter.

Context cost

Together Deploy Integration 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 90 tokens; SKILL.md has 403 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~90
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). 403 words, ~1,068 tokens.

Download SKILL.mdSave it as .claude/skills/together-deploy-integration/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
together-deploy-integration
description
Deploy and roll back Together AI integrations across serverless inference or v2 Dedicated Model Inference with secret injection, health probes, traffic control, and cost shutdown. Use when releasing Together-backed services or dedicated models. Trigger with "deploy Together", "Together dedicated endpoint", or "Together rollout".
allowed-tools
Read, Glob, Grep, WebFetch, Write, Edit
compatibility
Designed for Claude Code; deployment requires platform access and Together AI project authorization
argument-hint
[repository-path] [serverless|dedicated-v2] [environment]
version
1.9.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
saas, together-ai, deployment
model
inherit
effort
high

Together AI Deployment Integration

Overview

This skill separates application release from paid Together capacity changes and defines a reversible deployment for serverless or current v2 dedicated inference.

Prerequisites

  • A tested application artifact and model-quality evidence
  • Environment-scoped secret references and network egress policy
  • Current model availability plus serverless or dedicated capacity decision
  • Health, canary, rollback, cost, and teardown owners

Tool Discipline

Use Read, Glob, and Grep to inspect manifests, secret wiring, health checks, and rollback automation. Use WebFetch for current Together model and DMI lifecycle contracts. Use Write or Edit only for approved deployment files after the target platform is confirmed.

Current Contract

  • Serverless needs no GPU provisioning and uses the shared inference API with a current model ID.
  • New dedicated deployments use Together's v2 endpoint/deployment model and beta management surfaces.
  • Legacy v1 endpoint creation is retired; do not publish client.endpoints.create(model=..., hardware=...) as the new path.
  • Dedicated replicas bill while running. Scale to zero or delete after an approved rollback or experiment.

Authentication

Inject a project-scoped TOGETHER_API_KEY from the deployment platform's secret manager. Dedicated management also requires authorized project context; never expose management identifiers or Bearer headers unnecessarily.

Instructions

  1. Classify the workload as serverless or dedicated from latency, throughput, model, and utilization evidence.
  2. Pin the application artifact, SDK major, configuration schema, model policy, and secret references.
  3. For dedicated v2, resolve model/config resources, create the deployment, and poll to ready before routing traffic.
  4. Run a non-sensitive health probe that validates provider reachability and response shape.
  5. Shift a bounded canary while monitoring error rate, latency, usage, quality, and cost.
  6. Promote or roll back explicitly; scale obsolete dedicated replicas to zero and verify billing disposition.
Show full SKILL.md (126 more words)Show less

Approval Boundaries

Do not provision paid hardware, change traffic weights, rotate production keys, or promote a model without the named owners and an executable rollback.

Output

Return deployment mode, artifact/model/config identities, secret reference, readiness and canary evidence, traffic state, cost state, rollback result, and teardown owner.

Error Handling

ConditionResponse
Legacy v1 create returns 403Stop and migrate to the current v2 DMI flow.
Deployment ready but routing failsVerify traffic split and endpoint inference name.
Canary regressesRoute back and preserve redacted evidence.
Teardown unverifiedKeep the change open; dedicated replicas may still bill.

Examples

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

text
mode=dedicated-v2; deployment=ready; canary=5%; rollback=verified; obsolete-replicas=zero

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-deploy-integration of jeremylongshore/tons-of-skills-marketplace.

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

Open the folder on GitHubat commit cfae287

Compare with similar skills

Together Deploy Integration 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 Deploy Integration compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Together Deploy Integration this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.1kAutomated safety check: PassMIT
Tianji Worker Operationsmsgbyte/tianji3.1k—~1.1kAutomated safety check: PassApache-2.0
Deploy Verceljohnku2011/boilerplates-with-ai-skills240—~660Automated safety check: NotesMIT
Model Deploymentawslabs/agent-plugins916—~1.5kAutomated safety check: PassApache-2.0
AWS Serverless Deploymentawslabs/agent-plugins916—~1.3kAutomated safety check: PassApache-2.0
Cloud Provisioningelastic/agent-skills592—~5.4kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Together Deploy Integration

What does Together Deploy Integration do?

Deploy and roll back Together AI integrations across serverless inference or v2 Dedicated Model Inference with secret injection, health probes, traffic control, and cost shutdown. Together Deploy Integration is an agent skill from jeremylongshore/tons-of-skills-marketplace. Deploy and roll back Together AI integrations across serverless inference or v2 Dedicated Model Inference with secret injection, health probes, traffic control, and cost shutdown.

When should I use Together Deploy Integration?

Together Deploy Integration fits situations like: releasing Together-backed services; dedicated models; with deploy Together; together dedicated endpoint.

How do I install Together Deploy Integration in Claude Code?

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

How do I install Together Deploy Integration in Codex?

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

Can I use Together Deploy Integration 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-deploy-integration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/together-deploy-integration, .gemini/skills/together-deploy-integration, .github/skills/together-deploy-integration and .opencode/skills/together-deploy-integration in your project.

What does Together Deploy Integration need to run?

Going by SKILL.md and its folder, Together Deploy Integration needs credentials named TOGETHER_API_KEY. Our summary lists: 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; deployment requires platform access and Together AI project authorization.

Does Together Deploy Integration 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 Deploy Integration 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 Deploy Integration use?

Together Deploy Integration 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 Deploy Integration use?

About 1.1k tokens (SKILL.md is roughly 4.3k 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 Deploy Integration?

Skills that share tags, products or a category with Together Deploy Integration: Tianji Worker Operations (msgbyte/tianji, 3.1k stars), Deploy Vercel (johnku2011/boilerplates-with-ai-skills, 240 stars), Model Deployment (awslabs/agent-plugins, 916 stars) and AWS Serverless Deployment (awslabs/agent-plugins, 916 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Together Deploy Integration?

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.