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.
npx skills add TimoBakx/ai-journaling-template --skill weekly-reviewgit clone --depth 1 https://github.com/TimoBakx/ai-journaling-templateWrote 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/skills/timobakx/ai-journaling-template/weekly-review)<a href="https://agentmods.dev/skills/timobakx/ai-journaling-template/weekly-review"><img src="https://agentmods.dev/badge/skills/timobakx/ai-journaling-template/weekly-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/timobakx/ai-journaling-template/weekly-review"><img src="https://agentmods.dev/badge/skills/timobakx/ai-journaling-template/weekly-review.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00035 | $0.01951 |
| Opus 5.5 | $0.00014 | $0.00780 |
| Sonnet 5.5 | $0.00007 | $0.00390 |
| Haiku 4.5 | $0.00003 | $0.00195 |
Grade A, and why
weekly-review 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 17d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly Review
Weekly reviews are moments of deeper reflection: analyzing patterns, working out insights, making connections, and looking at where the learning goals were worked on and how the week relates to the expectation per component in work-evaluation/expectations.md.
When
- End of the week (Friday or the last moment of the workweek)
- Location:
week-evaluation.mdinside the week directory (journal/[YEAR]/[WEEK]/) - Template:
journal/weekly-review-template.md - Covers the full workweek
Always in its own session (see AGENTS.md, "One session per day"). Do not tack it onto a day session, not even when Friday has just been finished: the weekly review has to read and weigh the daily journals itself, not lean on whatever happens to still be in the conversation.
Preparation
- Read all daily journals of this week
- Read the previous two weekly reviews as context
- Read the week kickoff of this week
- Read
work-evaluation/expectations.mdfor the learning goals, the expectation per component and what is already listed under Above expectations and Dropped balls
Template sections
- 📅 This Week: overview per day with links and a short summary
- 🎯 Major Themes: the main subjects of the week
- 🎯 Work On Learning Goals: per learning goal: did I work on it this week, and if so, how (with links to the days). No status, no symbols. "Not this week" is an ordinary outcome.
- ⚖️ This Week's Weighing: the points from Above Expectations and Dropped Balls of the daily journals, grouped per component, with the source of recognition for above expectations and the fix for a dropped ball. Plus whatever the week analysis adds.
- 📚 Knowledge Sharing Check: what was learned or done that can be shared, and with whom?
- 🧠 Self-Insight & Profile Confirmations: brief
- 👀 Who Saw You This Week?: aggregation of the daily notes; empty = empty, that is data
- 🚩 Open Signals (Persistent): named needs, insights or observations that have not been addressed yet
- 🏢 Meeting Expectations: what simply went well, only when something stands out
- 🔄 Check Against This Week's Kickoff: to what extent did the week follow the kickoff document?
- 💡 Actions Next Week: concrete follow-up steps
- 🌟 Week Summary: the big reflection on the week
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.
- 17d ago First seen · 111 lines · 35 tokens per session scan A 28e354510ceb
weekly-review is a skill published in the GitHub repository TimoBakx/ai-journaling-template (34 stars, last pushed 18d ago), licensed MIT. It adds 35 tokens to every session and 1,951 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-15.
Other skills, from other repositories
orbit-notion
Open Orbit briefing skill — selected by the Orbit pipeline when Notion is the user's only connected connector, or when the user explicitly scopes their daily digest to Notion. Pulls the past 24 hours of document edits, comments, mentions, and database row changes from the user's authenticated Notion connection and…
agentmail
Use your assigned AgentMail inbox to read email tasks, explicitly send or reply, and check delivery. Provided automatically by your inbox assignment.
Cortex
LifeOS memory, prior-session recall, and learning capture. USE WHEN capture this learning, document this learning, what did we learn recently, recent learnings, cortex, knowledge, knowledge base, search knowledge, what do we know about, archive, harvest, knowledge status, develop note, add to knowledge, add a people…
rowboat-spaces
How to work as a member of Rowboat Spaces, the team chat where people and agents work together. Load it once per session, before acting on any request that reaches you from Rowboat; it covers your setup, mentions and hand-offs, the tools, and files.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
pinchtab-mcp
Use this skill when a task requires browser automation through PinchTab's MCP server connected to a remote browser instance. Covers navigation, element interaction, data extraction, form filling, multi-step flows, and session management via MCP tools.