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- AI Provider Migration & Compatibility Readiness Review
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AI Provider Migration & Compatibility Readiness Review
AI Provider Migration & Compatibility Readiness Review is a bounded ToolForge Labs workflow.
$8.99
AI Provider Migration & Compatibility Readiness Review
Example session with this skill installed
We plan to move a support assistant from one AI provider to another. It uses tools, JSON outputs, streaming, safety rules, retrieval context, and provider-specific retry settings. Review migration readiness and identify blockers before cutover.
- Read your context and instructions
- Compiled the ai provider migration
The likely issue is a contract mismatch around AI provider migrations, model identifiers, authentication, tool calling, structured outputs, streaming, token/context limits, safety settings, latency, fallback behavior, evaluation, observability, rollout, and rollback. I would first define the invariant: An AI provider migration is ready only when required application behavior, safety boundaries, tool/schema contracts, observability, cost/latency constraints, and rollback evidence are mapped and tested against the replacement provider. Then I would trace the smallest owning boundary, keep VERIFIED facts separate from LIKELY/UNKNOWN state, apply or propose the narrowest repair, and add deterministic normal, boundary, failure, retry/cancellation, and recovery tests. The workflow preserves authorization, privacy, security policy, public interfaces, user-visible behavior, and documented ownership. With repository/workspace access, findings can map to exact paths and focused local validation; with partial evidence, the result remains an explicit diagnosis/evidence map with no invented execution claims.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
AI Provider Migration & Compatibility Readiness Review is a bounded ToolForge Labs workflow. Diagnose and repair AI provider migrations, model identifiers, authentication, tool calling, structured outputs, streaming, token/context limits, safety settings, latency, fallback behavior, evaluation, observability, rollout, and rollback. Works from repositories/workspaces or partial evidence. Produces bounded fixes and deterministic validation while preserving authorization, security, public interfaces, user-visible behavior, and documented ownership and avoiding invented execution claims. It works from a full repository/workspace or partial evidence such as snippets, logs, configuration, traces, documents, tickets, and architecture notes. The skill separates verified facts from assumptions, avoids invented execution claims, and produces concrete repair/review steps with focused deterministic validation or traceable evidence.
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- 1
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- 2
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- 3
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