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    Technical Change Impact Review

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    Technical Change Impact Review is a bounded ToolForge Labs workflow.

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    Technical Change Impact Review

    Technical Change Impact Review

    Example session with this skill installed

    Review the impact of migrating the 'user-profile' service from Postgres to MongoDB based on the attached RFC and the 'profile-api' diff. Focus on data contracts and consumer impact.

    • Read your context and instructions
    • Compiled the technical change impact

    I have reviewed the RFC for the 'user-profile' migration and the current 'profile-api' diff. The review focuses on contract integrity and downstream consumer risk.

    Technical Change Impact Review: User-Profile Migration

    Impact AreaEvidence SourceStatusFinding/Gap
    Data Contractprofile-api diffConflictDiff shows removal of billing_address field, but RFC states "no schema deletions".
    ConsumersRFC Section 4.2VerifiedIdentified order-service and auth-gateway as direct consumers via gRPC.
    PersistenceRFC Section 2.1InferenceAssumes MongoDB Atlas handles retry logic; no driver config evidence in diff.
    RollbackNot foundGAPNo evidence of a data synchronization or reverse-migration plan.
    MonitoringRFC Section 6.0VerifiedNew Datadog dashboard user-prof-mongo-metrics is defined.

    Source Register

    • RFC-204: Service Migration Strategy (v2.1)
    • PR-452: profile-api schema changes
    • deps.json: Service dependency map

    Reviewer Questions

    1. Why is billing_address being dropped in the implementation when the RFC promises backward compatibility?
    2. Where is the rollback script stored? The RFC mentions a "migration tool" but no code exists in the current workspace.
    3. Has the order-service team signed off on the gRPC interface change identified in line 44 of the diff?

    Next steps

    • Reconcile the billing_address discrepancy between the RFC and the diff.
    • Document the data rollback strategy for the cutover window.
    • Request explicit sign-off from the order-service team regarding the interface change.

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    About this skill

    Technical Change Impact Review is a bounded ToolForge Labs workflow. Review technical change impact across dependencies, consumers, data/contracts, tests, rollout/rollback, ownership, and unresolved evidence. Works from supplied files, logs, tickets, reports, configuration, or architecture notes. Produces a traceable evidence review with explicit gaps and assumptions without inventing unavailable facts. It works from a full repository or partial evidence such as snippets, logs, configuration, traces, tickets, and architecture notes. The skill preserves existing product and security policy, separates verified facts from assumptions, avoids invented execution claims, and produces concrete repair or review steps with focused deterministic validation or traceable evidence.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Agents & Orchestration.

    Cannot verify production systems, external services, or facts that are not present in supplied evidence. With partial context it returns bounded diagnosis/review, explicit assumptions, and a deterministic validation plan rather than claiming successful execution.

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    Permissions

    Terminal / Shell
    Read Files
    Write Files

    Use a clean branch or a controlled review workspace. Supply repository files, logs, traces, configuration, or evidence needed for the task. Review all patches/findings before merge or operational action; keep production credentials and destructive production actions out of the workflow.

    Listed2 months ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill analyzes code, logs, and documentation to map how a specific technical change ripples through dependencies, data contracts, and rollout plans, preventing unforeseen outages caused by side effects.

    The skill accepts a wide range of inputs including full repositories, partial code snippets, system logs, Jira tickets, configuration files, and architecture diagrams to ensure a holistic review.

    It is compatible with most leading AI agents and LLM frameworks that support file-based analysis, and it functions as a modular workflow within the ToolForge Labs ecosystem.

    Unlike general AI code reviewers, this skill strictly separates verified facts from assumptions and refuses to 'hallucinate' or invent execution results, instead flagging explicit gaps in evidence for human review.

    Your purchase includes the workflow logic, configuration templates for various evidence types, and a guide for integrating the tool into your existing CI/CD or documentation pipeline.

    The output is a structured, traceable evidence review that outlines specific risks, identifies affected consumers, and provides concrete repair or validation steps to ensure a safe rollout.

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