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 djangonavarro220/agentic-life-os --skill routines-weekly-reviewgit clone --depth 1 https://github.com/djangonavarro220/agentic-life-osWrote 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/djangonavarro220/agentic-life-os/routines-weekly-review)<a href="https://agentmods.dev/skills/djangonavarro220/agentic-life-os/routines-weekly-review"><img src="https://agentmods.dev/badge/skills/djangonavarro220/agentic-life-os/routines-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/djangonavarro220/agentic-life-os/routines-weekly-review"><img src="https://agentmods.dev/badge/skills/djangonavarro220/agentic-life-os/routines-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 | $0.00024 | $0.00971 |
| Opus 5 | $0.00012 | $0.00485 |
| Sonnet 5 | $0.00005 | $0.00194 |
| Haiku 4.5 | $0.00002 | $0.00097 |
Grade A, and why
routines-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 12d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
routines-weekly-review
Mandatory integrity contract
Before acting, load and follow ../../references/data-integrity.md. Its provenance, missing-value, correction-history, defensive-write, backup, and recovery rules are mandatory for this subskill.
Run the weekly review as a guided meeting, not as a dashboard dump. This is the medium-speed loop: slower than heartbeat or a daily briefing, faster than monthly or quarterly resets.
The weekly review should gather due review items, ask one focused question at a time, and end with a compact set of decisions and next actions.
Trigger
Use for:
- scheduled weekly review routines
- weekly commitment and task review
- checking stale waiting items and blockers
- reviewing people/follow-up obligations
- reviewing review items whose cadence makes them due this week
- identifying repeated friction that should feed
system-improvement
Do not use this for deep quarterly direction setting or tiny status checks.
Review items
A weekly review is a container for due review items, not a fixed monolith. Review items may include:
- review what happened since the last review
- decide what should happen next week
- review active and waiting commitments
- inspect stale tasks or blockers
- review heartbeat candidates and noisy active watch targets
- inspect weekly-only domains or skills
- hand off repeated friction to
system-improvement
Each review item should have its own cadence, skip policy, and rough size. If a user changes heartbeat tuning from weekly to monthly, the weekly review should stop asking about it until it is due again.
Inputs to inspect
Use configured runtime-owned sources and Life OS pointers, for example:
- active and waiting tasks
- commitments and follow-ups
- recent daily briefing and heartbeat outputs
- calendar/deadline summaries if configured
- decision-journal items due for review
- review-item cadence and due-item records
- system-improvement backlog or recent friction notes
Read enough to decide what changed. Do not copy raw private logs into state.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 130 lines · 24 tokens per session scan A 9ca18a77d42d
routines-weekly-review is a skill published in the GitHub repository djangonavarro220/agentic-life-os (11 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 971 once invoked, about $0.0001 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 2026-08-30.
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