Coding Plus

    2

    Upgrade your AI agent with a senior-level engineering SOP focused on inspection, minimal diffs, and hard verification.

    $5

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    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    coding-plus

    Example session with this skill installed

    Analyze the login failure in auth.ts, identify the root cause, and provide a status update using the standard inspection headings.

    • Read your context and instructions
    • Compiled the coding-plus

    Verified

    • bug in auth.ts line 42
    • test failing with 401

    Inferred

    • fix requires middleware update

    Unknown

    • impact on legacy session tokens

    Residual Risk

    • haven't tested against Redis cluster failover.

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

    About this skill

    Elite Engineering Discipline for AI Agents

    Coding Plus transforms generic AI chat into a rigorous Senior Software Engineer's workflow. The primary challenge with AI coding is "hallucination-led development"—where models make assumptions about codebase state without looking at the files. This skill enforces an Inspect-First methodology that prioritizes verification over guesswork.

    What it does

    The skill embeds a Model-Agnostic Standard Operating Procedure (SOP) into your agent, ensuring every task follows a consistent lifecycle: deep inspection, contract definition, minimal diff implementation, and hard verification. It forces the agent to categorize every claim under specific Verified, Inferred, and Unknown headings, eliminating the ambiguity that leads to broken builds.

    Why use this skill?

    • Consistent Quality: Get senior-level output regardless of whether you are using GPT-4, Claude, or local models.
    • Reduced Technical Debt: Focuses on minimal diffs and preserving existing patterns rather than rewriting entire files.
    • Explicit Risk Reporting: The agent must admit what it hasn't tested, allowing you to focus your review on high-risk areas.
    • Universal Compatibility: Works across any language or framework (Node.js, Python, Go, etc.) by focusing on engineering logic rather than syntax.

    The Output

    Expect structured responses that include clear engineering success criteria and a dedicated "Residual Risk" report. No more "trust me" responses; you get actionable proof of what was run, what was fixed, and what remains to be seen.

    • High overhead for trivial tasks (e.g., typos).
    • Depends on the agent's ability to actually run file/shell tools.
    • May exceed token limits on very large file inspections.

    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.

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    Security scan passed 7 months ago

    Permissions

    Read Files
    Listed7 months ago

    What's inside

    Frequently Asked Questions

    coding-plus addresses 'hallucination-led development' by enforcing a rigorous 'Inspect-First' workflow that requires your agent to verify the actual state of your codebase before suggesting changes.

    This skill is model-agnostic and designed to work with any high-reasoning LLM (like GPT-4o or Claude 3.5 Sonnet) across any development environment that supports structured SOPs.

    Upon purchase, you receive the complete structured SOP and implementation guidelines that can be easily added to your agent's system instructions or knowledge base.

    Yes, coding-plus is language-agnostic because it focuses on engineering logic, verification protocols, and minimal diff principles rather than specific syntax.

    Unlike standard prompts, this skill forces the agent to categorize its knowledge into 'Verified,' 'Inferred,' and 'Unknown' data points, ensuring you know exactly where the agent is guessing.

    New in Code Quality & Review