More screenshots

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIDeepSeekDeepSeekMuseMuse+22 more

    System Change Verification & Post-Change Evidence Review

    1

    System Change Verification & Post-Change Evidence Review is a bounded ToolForge Labs workflow.

    $1

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned
    System Change Verification & Post-Change Evidence Review

    System Change Verification & Post-Change Evidence Review

    Example session with this skill installed

    We are changing a shared authentication policy across several services. The implementation plan exists, but the verification section is mostly 'watch dashboards'. Review what evidence is required before calling the change complete.

    • Read your context and instructions
    • Compiled the system change verification

    The likely issue is a contract or lifecycle mismatch around system change verification, preconditions, expected effects, post-change evidence, regression signals, rollback triggers, monitoring, ownership, and closeout. I would first state the invariant: A system change is verified only when intended effects and protected invariants are checked with explicit evidence, failure thresholds, and rollback ownership rather than inferred from absence of alerts. Then I would map VERIFIED evidence against the owning boundary, keep LIKELY/UNKNOWN state explicit, apply or propose the narrowest repair, and add deterministic normal, boundary, interruption, retry/cancellation, and recovery tests. With repository/workspace access, findings can map to exact paths and focused local validation; with partial evidence, the result remains a bounded evidence map with no invented execution claims.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    System Change Verification & Post-Change Evidence Review is a bounded ToolForge Labs workflow. Diagnose, review, and repair system change verification, preconditions, expected effects, post-change evidence, regression signals, rollback triggers, monitoring, ownership, and closeout. Works from repositories/workspaces or partial supplied evidence. Produces bounded fixes or evidence gates with deterministic validation while preserving authorization, security, public interfaces, user-visible behavior, and documented ownership, and never invents executed work. It works from a full repository/workspace or partial evidence such as snippets, logs, configuration, traces, documents, tickets, sample data, 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.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for LLM Ops.

    Cannot access live production environments. Requires manual input of environment-specific secrets or credentials. Focused on deterministic logic rather than probabilistic monitoring.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before buying a skill.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill goes through the trust checks below.

    Security scanned

    Checked by our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    Money-back guarantee

    Doesn't do what its page promises? You get your money back.

    Trust & safety

    Security scan

    Security scan passed 1 month ago

    Permissions

    Terminal / Shell
    Read Files
    Write Files

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

    Listed1 month ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill automates the verification of system updates by analyzing preconditions, expected effects, and post-change logs to ensure every deployment is stable and documented. It solves the problem of 'silent failures' and incomplete change evidence by identifying missing regression signals or rollback triggers.

    It is highly flexible, capable of working from full code repositories, local workspaces, or partial evidence like log snippets, architecture notes, and configuration traces. This makes it ideal for environments where full system access might be restricted or unavailable.

    No, the skill is built on a 'no-invention' policy, meaning it strictly separates verified facts from assumptions and never fabricates executed work or success signals. It produces deterministic validation gates that ensure your post-change evidence is based on actual system behavior.

    The skill is designed for compatibility with major AI agents and LLM-ops platforms that support ToolForge Labs workflows. It can be integrated into your existing CI/CD pipelines or used as a standalone diagnostic tool for reliability engineering.

    Upon purchase, you receive the full workflow configuration for System Change Verification & Post-Change Evidence Review, including the logic for diagnosing regression signals and ownership closeouts. Updates are provided periodically to ensure compatibility with evolving infrastructure standards and security protocols.

    New in LLM Ops