AI Agent Use Cases
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An agent that analyzes usage CSVs and defines cost-saving rules

The author gave 10 hours of usage CSV data back to Grok Bot for analysis and set 5 rules to reduce token use.

Grok Bot

How it works

  1. The author downloaded a detailed usage CSV from the usage page and asked Grok Bot to analyze it.
  2. The analysis counted 8,915 model calls and about 1.15 billion tokens. Conversations accounted for only about 11%; roughly 89% came from background tasks the bots launched themselves.
  3. The author applied 5 rules to all bots: wait no more than 5 minutes for subtasks, wrap up at around 120K context, allow at most 2 subtasks per bot, check no more often than every 5 minutes, and reduce screenshots.

Results

According to the analysis, 96% of input tokens went to rereading prior context, and calls exceeding 150K accounted for 54% of cost. The author expected the rules to save 25–30%, but this was an unmeasured estimate.

Notes

The savings are the author's estimate. The heaviest tasks reportedly involved 3D modeling with repeated screenshots and multiple PRs opened simultaneously.

Source

Reddit Original post ↗

Example prompt · Grok Bot

Analyze my AI bot usage records, identify where tokens are being spent, and suggest rules to reduce usage.

Inputs: usage CSV [file], analysis period [hours or dates], and bots and their assigned work [list]. First show the CSV columns and check whether conversations, background tasks, and cache reads can be distinguished. Mark anything that cannot be separated as unknown instead of guessing.

Analysis: 1) Calculate total calls and tokens. 2) Separate the proportion of conversations with me from tasks launched by the bots themselves. 3) Calculate context-size distribution per call and the share of cost attributable to large-context calls. 4) List the five tasks using the most tokens and explain why. 5) Identify when the largest number of tasks ran concurrently.

Deliverables: a numerical summary table, a list of costly tasks, and 3–5 draft bot rules with the estimated reduction range for each. Apply only rules I approve to bot settings, and label savings as estimates. Document the calculation method so the same analysis can be repeated a week later to check whether usage actually fell.