Analytical data doesn’t feed my ego; rather, it provides the foundation for defining strategies aimed at maximizing the return on any investment I make. HIVE is one such investment. It’s not about competing with others. It’s about competing with myself.
Analyzing statistics isn’t a matter of vanity or an “obsession with numbers”; it’s the difference between navigating with a compass and wandering aimlessly in an ecosystem where attention and capital (Hive Power) are finite resources. I’ve already mentioned this in this post.
I’d like to take this opportunity to update the list of tools [HivePulse by 
Time is a resource I like to optimize. I created this HIVE MONITOR tool for personal use, where I compile all the metrics I need to analyze in order to make decisions.
This way, I avoid having to jump back and forth between the various tools HIVE offers to evaluate performance. Browsers, links upon links, notes or mental records of results, refreshes upon refreshes—GONE. All thanks to the powerful Abacus.IA.
Every day, first thing in the morning, I receive a daily report via email about my activity on the HIVE blockchain.
When you ask Abacus.AI’s chatLLM for something, it distributes each request among more than 20 of today’s best digital brains—including Claude, ChatGPT, Grok, Kimi, Gemini, Deepseek, GLM, Perplexy Pro, and many others.
They have enough digital brains to scan the entire HIVE network and extract the information recorded on the blockchain. It accesses all available channels, and when those aren’t enough to fulfill the request—or are blocked for any reason—it creates agents to check every block executed on HIVE until it finds the answer to your command. It never gives up.
I created this Daily Report under the username 
It is identical to all the other tools available on HIVE. The blockchain is an open ledger—anyone can view it, but no one can delete it.
In addition to the date and time of the last update, it includes the basic information found on any of HIVE’s front-ends. With one new feature: When you hover over the KE, you can see whether there has been any compromise to the ecosystem or any external inflow of HIVE purchased on exchanges.
In this case, it’s my account. But as I mentioned earlier, I can analyze any HIVE user. I can find out, if applicable, how much HIVE the user purchased and sent to their wallet from exterior, and whether it came from an exchange or another wallet.
Similarly, the AI agent also scans the Hive-Engine and detects whether the user exchanged second-layer tokens for HIVE. Or whether they exchanged HBD for HIVE. Everything!
Given the current state of affairs, a user who buys HIVE—even if it’s just $5—and keeps it staked deserves the community’s respect. That commitment to the ecosystem deserves attention.
Since I have voting limitations (due to my modest HP), if I’m torn between two posts of similar quality, I’ll vote for the user who has already purchased HP and keeps it staked. Sorry, but once crypto prices improve, I’ll change my stance.
Total HIVE and HBD over the past 7 and 30 days, and the Daily Curation Rate — HIVE/day.
The percentage varies daily due to various factors. I like to analyze this metric, and every now and then I make it onto the Most Efficient Curators Ranking. That motivates me to stay on the right track to get a return on my investment.
This metric defines the quality of curation within the context of the Proof of Brain protocol. It is inspired by the ManteCurated Live (by 
This version displays decimal numbers in the CQS Score for the 7- and 30-day periods, making it more informative and accurate.
It is this metric that indicates who practices healthy curation, grounded in diversity and balance—contributing to the health of the ecosystem.
In this post (Maximize your vote), I discuss the importance of voting within 24 hours of publication. If you vote within 12 hours of publication, you may get better results before the most valuable votes are cast.
My modest HP (20K) limits the number of votes I have available, which means I have to manage them carefully. In the post I linked to earlier, you can read my stance on KE; I evaluate each case individually. I’m not a fundamentalist, but I’m not a sucker either. I set KE 4.00 as the limit for my curation, with very specific exceptions.
Reputation doesn't depend solely on how long you've been on HIVE; there are other factors. But it helps give an idea. I determined that accounts with a reputation of up to 70 would be considered new—up to 2 years of account history. This isn't mathematically exact.
I need to improve this aspect; the goal is to achieve a better balance.
The 7-day and 30-day calculations in HIVE and HBD.
The report concludes with recommendations generated automatically based on data from the period, including CQS and APR analyses.
These are the metrics I need to guide my strategies. I don’t intend to implement this tool in the ecosystem. Hive already has very good analytical tools; this one is for personal use.
I’ll end as I began: It’s not about competing with others. It’s about competing with myself.
