together-prod-checklist
Review a Together AI production release across model policy, auth, data controls, dynamic limits, retries, observability, cost, deprecations, asynchronous recovery, and rollback. Use when reviewing go-live or a material model change. Trigger with "Together production checklist", "Together go live", or "Together readiness review".
Allowed Tools
Provided by Plugin
together-pack
16 source-grounded operator skills for Together AI inference, batch, fine-tuning, deployment, security, and operations
Installation
This skill is included in the together-pack plugin:
/plugin install together-pack@claude-code-plugins-plus
Click to copy
Instructions
Together AI Production Checklist
Overview
This skill produces a release decision backed by current provider, application, security, reliability, quality, and cost evidence.
Prerequisites
- A pinned release artifact and environment configuration
- Model/endpoint quality, latency, availability, and cost thresholds
- Secret, data handling, monitoring, incident, and rollback owners
- Current Together model, limit, pricing, and deprecation evidence
Tool Discipline
Use Read, Glob, and Grep to inspect configuration, model policy, retry logic, tests, and runbooks. Use WebFetch for current Together contracts. Use Write or Edit only for approved remediation or the release record.
Current Contract
- Resolve model IDs and deprecation status at review time; do not trust an old README.
- Read dynamic limit headers and bound concurrency, tokens, retries, and queues.
- Separate serverless, batch, fine-tuning, and dedicated failure/recovery paths.
- Dedicated replicas require explicit cost shutdown; batches require output/error reconciliation.
Authentication
Verify environment-specific project keys, secret-manager injection, rotation/revocation, fork isolation, and log redaction. Never prove readiness by displaying a credential or authorization header.
Instructions
- Pin artifact, SDK major, configuration, model policy, and environment identity.
- Verify authentication, data classification, redaction, retention, and tenant isolation.
- Run offline tests and a bounded live canary for response shape, latency, quality, usage, and limits.
- Exercise
401,402,404,429,503, timeout, partial batch, and model-deprecation paths. - Reconcile spend forecasts with billing analytics and confirm alerts and dedicated teardown.
- Execute rollback/degradation evidence, assign all exceptions, and issue go, conditional-go, or no-go.
Approval Boundaries
Do not waive a failed security, quality, cost, or recovery control. Conditional approval must name the owner, deadline, monitoring, and rollback trigger.
Output
Return a control-by-control evidence matrix, exceptions, owners, current-provider snapshot, rollback result, cost state, and release verdict.
Error Handling
| Condition | Response |
|---|---|
| Model is deprecated or redirected | Re-evaluate behavior and migrate before go-live. |
| Live probe cannot run | Do not report it passed; issue an explicit exception or no-go. |
| Cost/usage is unreconciled | Block capacity changes and assign the billing owner. |
| Rollback fails | No-go until a recoverable path is proven. |
Examples
The example below shows the minimum redacted evidence expected from a successful invocation of this operator workflow.
artifact=pinned; auth=pass; model=current; limits=measured; rollback=pass; verdict=go