NickKnightAI

1 - Second Brain : Useful for context engineering. It shows what eats your window, for example huge shell outputs, screenshots or re reading the same files. It also shows how close the session is to an auto compaction, and whether the agent is still exploring (lots in, few actions) or executing. Over this whole session, the agent's own output (828k tokens) and cache rebuilds (459k) were the largest inputs. 2 - Memory: for instruction adherence. It shows which constraints the agent keeps using (BACKEND was recalled 38 times over the whole session) and which it never mentions again. A decision with zero recalls may have been forgotten. It also shows whether your decisions were written down somewhere that survives a compaction or a new session. Note: a recall is a text match of the fact in what the agent wrote, not proof that it acted on it. 3 - File swarm: to change impact and review. It shows the blast radius (which files changed and which were only read), provenance (what was ported from where), the dependency structure, and churn (the same file edited again and again). It also shows how full the context gets while the agent juggles many files 4 - Tool timeline: for performance and reliability. It shows slow tools and long builds, failing commands and retries, loops, bursts against steady work, and how long the agent waited for you (the idle folds). 5 - Cost lab: Prices are list prices per token type, calibrated to the session's own cost record, so the total matches what was billed ($69.98). To maintain the cost control. It shows what drives spend (here, re-reading a large context every turn), the price of a compaction, and the price of leaving a session idle longer than the cache lasts (the $1.19 rebuild). It also shows which phases were expensive and gives a burn rate for budgeting. 7 - Terminal idle: Useful for: an audit trail. You can see the exact order of commands and edits, where things failed and how they were fixed, what was committed, and when you stepped in to approve or redirect.