Structured Cost Audits: Electricity, Travel, Returns & Budgets
A strict workflow for auditing variable costs using read-only prompts that extract hard numbers and flag ambiguities without guessing.
Structured Cost Audits: Electricity, Travel, Returns & Budgets es un pack curado del arsenal de TokRepo — 4 recursos de IA seleccionados a mano para que instales toda la pila con un único comando. Cada recurso ha sido verificado en vivo (estado público, descarga vigente), etiquetado por tipo principal y curado para funcionar junto a los demás del pack.
Para instalar, ejecuta `tokrepo install pack/tokrepo-editorial-cost-saving-c1d6d81179d8` en tu terminal — o pasa el mismo comando a tu agente IA (Claude Code, Cursor, Codex CLI, Gemini CLI, GitHub Copilot, Cline, Roo Code y Windsurf están todos soportados). El TokRepo Node CLI obtiene cada recurso del registro, coloca los archivos de skill en `.claude/skills/`, los prompts en tu directorio de prompts, los servidores MCP en la configuración del cliente, y muestra un resumen de lo instalado.
Sin un pack, tendrías que descubrir, validar e instalar cada uno de estos 4 recursos uno por uno — normalmente entre 30 y 60 minutos por recurso. El pack reduce eso a un solo comando, y se mantiene actualizado a medida que los recursos subyacentes se vuelven a publicar. Si algún recurso pasa a privado o se elimina, el pack lo detecta automáticamente y omite esa entrada en la siguiente instalación — no hay paquetes rotos.
Cómo usar esta colección
This collection provides a practical workflow for saving tokens and preventing costly errors by replacing open-ended queries with strict, table-based comparison prompts. Open-ended questions often lead to verbose, hallucinated responses that burn through your budget. By contrast, these prompts constrain the model to specific columns, forbid guessing, and require explicit labeling of unknowns. Step 1: Local Service Fairness Check. Use the 'Compare Local Service Listings' prompt when you have scattered text from websites or emails. Paste the raw listings. The prompt forces the AI to extract hours, fees, and eligibility into a fixed table. It will not average prices or invent phone numbers. This prevents the AI from writing a long, opinionated summary that wastes tokens on irrelevant fluff. You get a clean draft to review before making calls. Step 2: Electricity Tariff Audit. Use the 'Electricity Tariff Comparison Analyst' prompt when switching providers. Paste your current tariff JSON baseline and the raw text from a new contract. The prompt extracts fixed daily charges and unit rates (including peak/off-peak if applicable). It compares these against your baseline and flags ambiguous clauses like 'subject to market adjustment'. It does not calculate projected bills based on assumed usage, ensuring you only pay for precise structural comparisons. Step 3: E-Commerce Return Policy Check. Use the 'E-Commerce Return Policy Auditor' before initiating a return. Paste the receipt text or order confirmation email. The prompt extracts critical fields: return window, start date trigger, condition requirements, restocking fees, and return shipping costs. It calculates estimated deadlines and flags risks like 'buyer pays shipping' or '10% restocking fee'. It never contacts sellers or generates labels; it provides a risk assessment to help you decide if the return is financially viable. Step 4: Household Budget Anomaly Detection. Use the 'Read-Only Budget Anomaly Brief' for monthly reviews. Paste transaction rows with headers. The prompt acts as a read-only auditor, flagging duplicates or outliers with confidence levels. It never edits files or executes payments. It produces a concise brief for human review, avoiding the high token cost of full financial analysis or open-ended chat about spending habits. Prerequisites: A plain-text AI chat interface. No API keys or software installation required. Limitations: These prompts are drafting and auditing tools. They do not browse live websites, check real-time prices, or execute transactions. Always verify final numbers with original source documents. Examples provided are fictional and for structural reference only.
4 recursos listos para instalar
Motivo de la selección:Serves as the foundational step for local research. It replaces vague summaries with a strict table of stated hours and fees, preventing the AI from wasting tokens on invented contact info or subjective rankings.
Motivo de la selección:Extracts fixed fees and unit rates from electricity contracts, comparing them against a baseline to identify structural cost differences without calculating speculative bills.
Motivo de la selección:Audits e-commerce receipts for hidden return costs like restocking fees and shipping liabilities, preventing costly return errors.
Motivo de la selección:Provides a safe, read-only audit mechanism for budgets. It flags anomalies like duplicate charges without editing source data, offering a concise brief for human review that avoids the high token cost of open-ended financial advice.
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