u/dericksc

I created an aggregator for brute force login attacks across a number of websites I own. As the site approaches two years, the leaderboard is dominated by Digital Ocean IP addresses. If you have a single IP address with over 100K attacks being issued from it, you'd think a circuit breaker would trip somewhere in the monitoring stack.

The Irony? Each of the sites reporting they were being brute forced are ALSO hosted on Digital Ocean Droplets!! The firewall rules of the attacked droplets only allow port 443 access through CloudFlare meaning this is not happening on internal IP addresses. Hence, the title of this post The Attack from Within!

Data published on https://bruteforce.live

https://bruteforce.live

I designed and built RESERVE CLI to fill a gap in macroeconomic data workflows. It’s a command-line toolbox built around the Federal Reserve’s FRED® API. I also used it as a playground for AI-assisted onboarding—focused on making commands more discoverable by surfacing intent, context, usage patterns, pipeline examples, and common gotchas.

This post discusses how expanding the user surface area to include agents required the command model and overall application to be architected for both usability and deterministic outputs.

Classic CLI Behavior - Human and Applications as Consumers

Run commands and sub-commands with stdio output piped to tables, json, or csv formats. Pipelining allows commands to pass output to other commands. Standard Unix Philosphy:

>"Do one thing well and work well with others."

Agentic Behavior - Agents Onboard and Run Chained Commands

Open Visual Studio Code, Warp Terminal, or Codex and prompt:

>I have a CLI named RESERVE on this system. Run 'reserve onboard' to get yourself up to speed. Then get ready for some macroeconomics questions.

Next, go simple:

>Can you tell me about the consumer price index in 2022?

reserve obs get CPIAUCSL --start 2022-01-01 --end 2022-12-31 --format jsonl | reserve analyze summary

or go complex:

>Can you tell me about the credit regime in 2008?

reserve obs get FEDFUNDS DRCCLACBS T10Y2Y UNRATE --start 2008-01-01 --end 2008-12-31 --format jsonl

MCP vs. CLI - Pushing Determinism to the Right

In the previous examples, an agent running RESERVE commands interprets the data it receives. That raises a natural question: wouldn’t it be better for an agent to connect directly to the data API via an MCP server?

The short answer is: sometimes—but deterministic preprocessing yields more reliable results.

Consider a simple example. Given a file with 100 tab-delimited rows of fruits and vegetables, the following pipeline will produce the same output every time:

grep FR list.txt | sed 's/\tFR$/\tFruit/'

However, order of operations matters:

sed 's/\tFR$/\tFruit/' list.txt | grep FR

This returns nothing, because the transformation removes the very pattern the downstream command depends on.

The commands are identical—only the order changes—but the result is completely different.

Now imagine an agent accessing the same data through an MCP interface. It could arrive at an answer through multiple possible execution paths, each with varying levels of transparency. Without a clearly defined sequence of transformations, reproducibility becomes harder to guarantee.

For complex domains like macroeconomic analysis, this matters. CLI-based workflows enforce explicit, deterministic transformations—pushing ambiguity as far right as possible. By the time data reaches an LLM, it has already been filtered, shaped, and validated in a repeatable way, improving both interpretability and trust in the final output.

That said, CLIs are not immune to order-of-operations mistakes. As shown earlier, simply reordering commands can completely change—or invalidate—the result. Most help documentation focuses on individual commands in isolation, not on how they behave when chained together in real workflows. This is where thoughtful onboarding and richer command discoverability pay dividends, helping users understand not just what a command does, but how it behaves in a pipeline.

What's Next

In an upcoming release, concurrent series downloading will be paired with an upgraded analyze command set for per-series processing.

Below is a Notebook LM created infographic that captures the design goals. More use case information is available at https://reservecli.dev . Feedback is always welcome.

RESERVE Command-Line Interface for FRED® Macroeconomic Data