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    Agentic Workflow

    4

    A risk-aware, evidence-based engineering lifecycle protocol for robust agentic task execution and safety.

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    23 uses5.0 (1 review)

    agentic-workflow

    Example session with this skill installed

    Upgrade the project to Node v20, ensure all existing unit tests pass, and stage the changes for my review. Do not push to the remote repository.

    • Read your context and instructions
    • Compiled the agentic-workflow

    Verification

    • Passed: Unit tests, linting
    • Failed: 0
    • Environment Delta: Node v18 -> v20
    • Dependency Scan: Clean

    Summary Report

    • Commits pending push: [a1b2c3d, e4f5g6h]
    • Status: Verified & Awaiting human push. Agent did not push to remote.

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

    About this skill

    What it does

    The Agentic Workflow is a language-agnostic, risk-aware protocol designed to prevent the four most common AI agent failures: silent assumptions, scope creep, untested deployments, and credential leakage. It transforms vague requests into evidence-based execution by enforcing a multi-stage engineering lifecycle similar to a senior dev's mental model.

    Why use this skill

    Prompting an AI often results in "hallucinated" progress or unexpected side effects. This skill forces your agent to follow a structured discipline of research, planning, safety-gating, and verification. It is better than raw prompting because it includes built-in guardrails like cascading failure detection, secret scanning, and an absolute "never push" rule for production stability.

    Supported tools

    • Development Environments: Works inside or outside Git worktrees with filesystem fallback.
    • Frameworks: Language-agnostic (Python, Go, Node, Rust, etc.).
    • CI/CD: Comprehensive verification matrices and rollback planning.
    • Safety: Integrated secret scanning and shell quoting safety protocols.

    The Output

    Instead of just code, you receive an audit-ready closure report including a Risk Class assessment, a Verification Matrix (Passed/Failed/Unstable), a Scope Check (Planned vs. Actual changes), and a Rollback Strategy. It ensures all work is staged, verified, and ready for human approval.

    • Not for chat-only tasks (requires file/terminal access).
    • No production deployments (enforces manual push).
    • Requires clear repository signals to avoid generic assumptions.

    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 any payment.

    Reviews

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    This skill has been used 23 times.

    Trust & safety

    Security scan

    Security scan passed 6 months ago

    Permissions

    Terminal / Shell
    Listed6 months ago

    What's inside

    Frequently Asked Questions

    This skill is language-agnostic and functions effectively across Python, Go, Node.js, and more by utilizing filesystem-based protocols and standard shell environments.

    It implements a rigid engineering lifecycle including secret scanning, risk-class assessments, and a "never-push" rule to ensure AI agents cannot make unverified changes to production environments.

    The skill provides a protocol that can be integrated into most modern AI agent frameworks; it requires the agent to have filesystem access and the ability to execute shell commands for verification.

    Unlike standard prompts, this workflow enforces a multi-stage audit trail featuring a Verification Matrix and Scope Check, ensuring every action is backed by evidence rather than assumptions.

    You will receive the full protocol logic, the risk-assessment framework, and the verification templates required to transform your agent into a disciplined, senior-level engineering assistant.

    The skill is designed with a fallback mode that allows it to maintain the same rigorous safety and verification standards even when working outside of a standard Git environment.

    New in Agents & Orchestration