Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/fatihkan/badiWrote 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/fatihkan/badi/dashboard)<a href="https://agentmods.dev/commands/fatihkan/badi/dashboard"><img src="https://agentmods.dev/badge/commands/fatihkan/badi/dashboard.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 | $0.00000 | $0.00698 |
| Opus 5 | $0.00000 | $0.00349 |
| Sonnet 5 | $0.00000 | $0.00140 |
| Haiku 4.5 | $0.00000 | $0.00070 |
Grade A, and why
dashboard 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 today.
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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Daily statistics panel. Presents task, audit, event, and performance data as a unified table.
Required Tools
- Bash (date calculations, file statistics)
- Read (TaskBoard.md, audit-trail.md, incident-log.md, failure-log.md, daily notes)
- Grep (data extraction and counting)
- ...
Data Sources
This command collects data from the following files:
TaskBoard.md- Task status informationaudit-trail.md- Audit trail recordsincident-log.md- Incident records- ...
Section 1: Task Statistics
Step 1: Read the TaskBoard Data
- Read
TaskBoard.md - Count the task states:
- Done (DONE)
- In Progress (IN_PROGRESS)
- Waiting (TODO)
- Blocked (BLOCKED)
Step 2: Today's Task Movement
- Filter tasks completed today
- Detect new tasks created today
- List tasks whose status changed
- ...
Section 2: Change Statistics
Step 3: Audit Trail Analysis
- Read
audit-trail.md - Filter entries matching today's date
- Extract the changed file count
- ...
Step 4: Git Statistics
- Get today's commit count with
git log --since="today" --format="%H" | wc -l - Compute the change size with
git diff --stat HEAD~[count] - Report added and removed line counts
Section 3: Incident and Failure Statistics
Step 5: Review the Incident Records
- Read
incident-log.md(if present) - Filter today's incidents
- Extract the severity distribution:
- CRITICAL: production-impacting
- HIGH: affects important functionality
- MEDIUM: limited impact
- LOW: cosmetic or small issues
Step 6: Review the Failure Records
- Read
failure-log.md(if present) - Filter today's failures
- Detect recurring failure patterns
- ...
Section 4: Session Length Estimate
Step 7: Duration Calculation
- Find the first entry in audit-trail.md or the daily notes (session start)
- Find the last entry (now or the latest activity)
- Compute the difference
- ...
Section 5: Weekly Comparison
Step 8: Collect Last Week's Data
- Find last week's same-day statistics (if available)
- Comparison metrics:
- Completed task count
- Commit count
- Incident/failure count
- Work duration
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.
- today First seen · 117 lines · 0 tokens per session scan A 9f9c3c99326a
dashboard is a command published in the GitHub repository fatihkan/badi (7 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 698 tokens. 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 2026-09-06.
Other commands, from other repositories
plan-start
5-phase planning command: PRD analysis, design review, technical decisions, dynamic research team, metrics. Produces a complete implementation plan + ADRs before any code is written.
plan-ceo-review
Strategic product gate — challenge the brief, find the 10-star product hiding inside the request, before writing any code.
routines-discover
Analyzes the current project to surface high-value Routines use cases across the three trigger types (schedule, API, GitHub events). Usage: /routines-discover.
check-cache-bugs
Audit Claude Code setup for cache bugs (CC#40524) — sentinel, --resume/--continue, attribution header + ArkNill B3/B4/B5.
review-pr
Perform a comprehensive code review of a pull request.
git-worktree-clean
Clean up stale git worktrees with merged branch detection and disk usage report.