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/wrap-up)<a href="https://agentmods.dev/commands/fatihkan/badi/wrap-up"><img src="https://agentmods.dev/badge/commands/fatihkan/badi/wrap-up.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 | $0.00684 |
| Opus 5 | $0.00000 | $0.00342 |
| Sonnet 5 | $0.00000 | $0.00137 |
| Haiku 4.5 | $0.00000 | $0.00068 |
Grade A, and why
wrap-up 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.
End-of-day ritual command. Prepares the day for closure and sets the stage for tomorrow.
Required Tools
- Read (memory, notes, logs)
- Write (updates and report writing)
- Bash (git status, task checks)
- Grep (event scan)
Procedure (11 Steps)
Step 1: Read the State
- Read
memory.md - Read the daily note (
daily-notes/DDMMYY.md) - Check the task board
- Review the git status (uncommitted changes)
Step 2: Process the Ledger
Compile the day's events:
- Commits and changes made
- Decisions taken and their rationale
- Problems hit and their solutions
- Directions given by the user
Step 3: Synchronize Memory
Update memory.md:
- Add new learnings
- Remove stale information
- Update the project state
- Record important decisions
Step 4: Move Completed Tasks
- Mark finished tasks as "completed"
- Add the completion date
- Update the status of partially finished tasks
- Note blocked tasks and their reasons
Step 5: Export Learnings
Record today's lessons:
- Technical learnings (new APIs, patterns, tools)
- Process learnings (what worked / what did not)
- Project insights
- Add them to
knowledge-base.md
Step 6: Run the Auditor
Do a quick T1 audit:
- Any uncommitted changes?
- Any broken tests?
- Any temp files or debug code left behind?
- Anything carrying a security risk?
Step 7: Review the Event Log
- Order the day's important events chronologically
- Anything abnormal or needing attention?
- Flag topics that need follow-up
Step 8: Preview Tomorrow
- Determine tomorrow's priority tasks
- Check dependencies (work waiting on someone else)
- Any calendar events or deadlines?
- List the suggested focus areas
Step 9: Update the Daily Notes
Complete the daily-notes/DDMMYY.md file:
## End-of-Day Summary
- Completed: [list]
- In Progress: [list]
- Deferred: [list]
- Tomorrow's Priority: [list]
## Learnings
- [learnings]
## Decisions
- [decisions and their rationale]
Step 10: Coach Analysis (Fridays)
If it is Friday, run the weekly coaching analysis:
- Weekly productivity summary
- Progress toward goals
- Energy and focus patterns
- Suggestions for next week
- Wins to celebrate
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 4d41e3ace132
wrap-up 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 684 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.
session-save
Save the current session state — decisions, modified files, current status, and next steps — to a handoff file for later resume.
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.