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Automation
Command

/brain-stats

Show claudectl brain learning metrics — accuracy, correction rate, and effectiveness

From plugin
claudectl
1957 skills1 agent7 commands1 MCP
Install
$ npx -y skills add mercurialsolo/claudectl --agent claude-code

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/brain-stats

Context preview

What this command does when you run it.

Show claudectl brain learning metrics — accuracy, correction rate, and effectiveness

Command definition

brain-stats.md
name: brain-stats
description: Show claudectl brain learning metrics — accuracy, correction rate, and effectiveness
args: "[metric]"

Show how well the claudectl brain is learning the user's preferences. The optional argument selects a specific metric view.

Available metrics (pass as argument, or show all if omitted):

  • `learning-curve` — is the correction rate declining over time? (= brain is learning)
  • `accuracy` — per-tool, per-risk, per-project accuracy breakdown
  • `baseline` — brain vs. dumb static rules classifier comparison
  • `false-approve` — safety metric: how often does brain approve risky actions that get rejected?

Run the appropriate command:

  • All metrics: run `claudectl --brain-stats learning-curve` then `claudectl --brain-stats accuracy`
  • Specific metric: run `claudectl --brain-stats {{metric}}`

Present the results highlighting:

  • Whether the brain is improving over time
  • Which tools the brain handles well vs. poorly
  • Any safety concerns (high false-approve rates)
Ships withclaudectl

Orchestrate a swarm of Claude Code agents with a local brain that learns from you.

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Rust
Language
MIT
License
1mo ago
Last commit
4mo ago
Created

Repo: mercurialsolo/claudectl