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    Forfait Nacalculatie

    5

    Automated profitability analysis and fee-review signaling for flat-fee accounting client portfolios.

    $7

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    Example session with this skill installed

    Analyze our annual flat-fee clients from clients_2023.csv using an hourly rate of €110. Identify which dossiers are loss-making and suggest discussion points for the fee review.

    • Read your context and instructions
    • Compiled the forfait-nacalculatie
    • Generated the data export

    Analysis complete for 45 clients.

    • 6 dossiers flagged as "Loss-making" (<80% coverage).
    • BVBA Janssen: 62% coverage (Fee €4k vs Value €6.4k). Discussion: Scope creep in VAT?
    • Total Firm Coverage: 92%.
      Full breakdown saved to nacalculatie_summary.csv.

    nacalculatie_summary.csv

    CSV · data export

    Generated

    Example file from a real run - the skill writes it into your workspace.

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

    About this skill

    Automated Profitability Analysis for Accounting Firms

    As accounting firms move toward fixed-fee (flat-fee) pricing, monitoring the gap between fees and actual time investment is critical. This skill provides a specialized Python-based workflow to calculate "nacalculatie" (post-calculation) for your client portfolio, identifying exactly which files are underperforming and why.

    What it does

    The tool processes client data—including annual fees and hours logged—to calculate key performance indicators per dossier. It generates a detailed report sorted by coverage percentage, highlighting files that require immediate attention.

    • Coverage Analysis: Compares fixed fees against hourly value.
    • Efficiency Metrics: Calculates effective hourly rates per client.
    • Automated Flagging: Triggers signals for loss-making dossiers (<80%), undervalued files, and high-margin outliers that might indicate service risks.
    • Decision Support: Provides a structured framework for price revisions and scope discussions.

    Why use this skill

    Manually auditing an entire client list for profitability is time-consuming and prone to oversight. This skill automates the math while providing the professional context needed for partner-level decisions. It goes beyond simple arithmetic by forcing the AI to consider "why" a dossier is loss-making—distinguishing between one-time peaks (e.g., audits) and structural scope-creep.

    Output format

    The primary output is a processed CSV file ready for Excel/PowerBI, accompanied by a high-level executive summary of the firm's total coverage and a prioritized 'action list' of the most critical files to review before the next billing cycle.

    Built by Nex AI. More skills and info at nex-ai.be and slopsome.com.

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

    • Requires pre-formatted CSV input with hours and fees.
    • Does not link directly to live accounting APIs.
    • Assumes linear hourly value without seniority weighting.

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    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.

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    Permissions

    Terminal / Shell
    Read Files
    Write Files

    Terminal/Shell: the agent runs the bundled Python script (argparse CLI). Read/Write Files: the script reads user-supplied local input files (CSV/JSON) and writes the result to a user-specified path. No network access, no environment variables, no secrets.

    Listed5 months ago
    Updated3 months ago

    What's inside

    Frequently Asked Questions

    This skill automates the comparison between your fixed-fee agreements and the actual hours logged, identifying 'loss-making' dossiers where time investment exceeds the fee and highlighting structural scope-creep.

    You will receive a specialized Python workflow designed for accounting data processing, along with a structured template for your input data and documentation on interpreting the profitability flags.

    The skill outputs a clean CSV file optimized for Excel or PowerBI, plus an executive summary and a prioritized 'action list' for your next fee-review meeting.

    While designed for standard accounting exports, the input template is flexible; you simply need to provide client IDs, total fees, and logged hours for the workflow to generate its analysis.

    Periodic updates are provided to adjust for evolving industry benchmarks and to ensure compatibility with the latest versions of the supported AI agent platform.

    Yes, the skill is capable of processing your entire client portfolio in one batch, allowing for a firm-wide overview of total coverage and effective hourly rates.

    New in Finance & Accounting