gemini-cost-trackerlisted

# Gemini Cost Tracker Use this skill when repeated Gemini calls need transparent token and cost accounting. It records usage metadata after each call and prints a simple per-model session summary. ## When to invoke - User says: "track gemini cost" / "gemini token usage" / "how much is this LLM call costing" - Code in the conversation uses: `google-genai`, Gemini REST responses, or repeated model calls in a batch. ## When NOT to invoke - The user only makes one or two ad hoc calls per day. - The user needs provider billing reconciliation rather than a local estimate. ## Concrete example User input: ```text Wrap this three-call Gemini ranking job so I can see model cost by session. ``` Output: ```python # Copy assets/cost_tracker.py into your project, then: from cost_tracker import CostTracker tracker = CostTracker() # resp = client.models.generate_content(model="gemini-2.5-flash", contents=prompt) tracker.record("gemini-2.5-flash", resp.usage_metadata) print(tracker.summary()) ``` Example printed output: ```text Calls: 3 | Total: $0.001242 gemini-2.5-flash-lite: $0.000180 gemini-2.5-flash: $0.001062 ``` ## Pattern to apply 1. Keep a small pricing table in USD per 1M tokens and mark it "verify before trusting." 2. After each Gemini call, read `usage_metadata` from the SDK response or `usageMetadata` from REST. 3. Subtract cached tokens from billable input tokens. 4. Count output plus thinking tokens at the output-token price. 5. Append one row per call and