Borrowing it
Nothing to install: this file belongs to plipowczan/claude-piv-skeleton. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/plipowczan/claude-piv-skeleton/main/.claude/commands/validation/learning-status.mdgit clone --depth 1 https://github.com/plipowczan/claude-piv-skeletonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/plipowczan/claude-piv-skeleton/learning-status)<a href="https://agentmods.dev/commands/plipowczan/claude-piv-skeleton/learning-status"><img src="https://agentmods.dev/badge/commands/plipowczan/claude-piv-skeleton/learning-status.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00006 | $0.00721 |
| Opus 5 | $0.00003 | $0.00360 |
| Sonnet 5 | $0.00001 | $0.00144 |
| Haiku 4.5 | $0.00001 | $0.00072 |
Grade A, and why
learning-status scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learning Status: View Learning Metrics Dashboard
Purpose
Display the current state of the learning system:
- Total reviews analyzed
- Issue trends by category and severity
- Recurring issues that need attention
- Applied improvements and their effectiveness
- Learning effectiveness metrics
Process
Step 1: Read Metrics
Read .claude/agents/learning/learning-metrics.md
Step 2: Display Dashboard
Format and display the metrics in a user-friendly format:
╔══════════════════════════════════════════════════════════════╗
║ LEARNING METRICS DASHBOARD ║
╠══════════════════════════════════════════════════════════════╣
║ Last Updated: {timestamp} ║
║ Reviews Analyzed: {N} ║
╠══════════════════════════════════════════════════════════════╣
║ ISSUE TRENDS ║
╠─────────────┬───────┬────────────────┬───────────────────────╣
║ Category │ Total │ Last 5 Reviews │ Trend ║
╠─────────────┼───────┼────────────────┼───────────────────────╣
║ Logic │ {N} │ {N} │ {↑↓→} ║
║ Security │ {N} │ {N} │ {↑↓→} ║
║ Performance │ {N} │ {N} │ {↑↓→} ║
║ Quality │ {N} │ {N} │ {↑↓→} ║
╠══════════════════════════════════════════════════════════════╣
║ RECURRING ISSUES (Need Attention) ║
╠══════════════════════════════════════════════════════════════╣
║ 1. {Issue title} - {N} occurrences ║
║ 2. {Issue title} - {N} occurrences ║
╠══════════════════════════════════════════════════════════════╣
║ IMPROVEMENT SUGGESTIONS ║
╠──────────────┬──────────┬─────────────────────────────────────╣
║ Generated │ Applied │ Pending ║
║ {N} │ {N} │ {N} ║
╠══════════════════════════════════════════════════════════════╣
║ LEARNING EFFECTIVENESS ║
╠══════════════════════════════════════════════════════════════╣
║ Issues Prevented (est.): {N} ║
║ Rules Updated: {N} ║
║ Skills Enhanced: {N} ║
╚══════════════════════════════════════════════════════════════╝
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 86 lines · 6 tokens per session scan A eda91478a16f
learning-status is a command published in the GitHub repository plipowczan/claude-piv-skeleton (4 stars, last pushed 7mo ago), licensed MIT. It adds 6 tokens to every session and 721 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
sdd-init
Initialize SDD context — detects project stack and bootstraps persistence backend.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.
argos
A command for checking whether an implementation matches its design deliverables. Its Korean description compares the work to the design as part of a completion inspection.