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 natea/ExoMind --skill monthly-reviewgit clone --depth 1 https://github.com/natea/ExoMindWrote 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/natea/exomind/monthly-review)<a href="https://agentmods.dev/skills/natea/exomind/monthly-review"><img src="https://agentmods.dev/badge/skills/natea/exomind/monthly-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/natea/exomind/monthly-review"><img src="https://agentmods.dev/badge/skills/natea/exomind/monthly-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 | $0.00000 | $0.08278 |
| Opus 5 | $0.00000 | $0.04139 |
| Sonnet 5 | $0.00000 | $0.01656 |
| Haiku 4.5 | $0.00000 | $0.00828 |
Grade A, and why
monthly-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 5d 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 — 1,234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monthly Review
Overview
Conduct comprehensive monthly reviews that aggregate insights from weekly reviews, track goal progress, assess life areas, and plan for the next month. This skill implements a 4-phase process that transforms weekly data into actionable monthly insights.
Purpose
- Aggregate and analyze patterns from 4-5 weekly reviews
- Measure progress on quarterly OKRs and monthly goals
- Check in on all life areas from latest assessment
- Identify trends, wins, and recurring challenges
- Plan priorities and focus areas for next month
- Build momentum through pattern recognition
Prerequisites
- At least 3-4 completed weekly reviews for current month
- Active quarterly goals/OKRs in memory/plans/active-plan.md
- Latest life assessment in memory/assessments/
- Access to memory/weekly/YYYY-WNN.md files
Trigger Timing
- Last day of month: Comprehensive monthly review
- Emergency review: Any time when significant course correction needed
- Quarterly alignment: Month 3 review includes quarterly assessment
The 4 Monthly Review Phases
Phase 1: COLLECT - Gather Monthly Data (10-15 min)
Objective: Aggregate all weekly reviews and relevant data for the month.
Steps:
-
Pull all weekly reviews:
- Read memory/weekly/YYYY-W{01-05}.md for current month
- Extract: wins, challenges, completions, habits, insights
- Note which weeks had patterns
-
Gather goal tracking:
- Read memory/plans/active-plan.md
- List all OKRs and monthly goals
- Pull completion percentages from weekly reviews
-
Collect life area data:
- Read memory/assessments/latest.md
- Review scores for all 10 life areas
- Note any red flags (<5) or improvements
-
Review calendar highlights:
- Significant events, meetings, milestones
- Time off, travel, major disruptions
- Energy patterns (high/low weeks)
Output: Aggregated data file ready for analysis
Phase 2: ANALYZE - Identify Patterns (15-20 min)
What ships with it
2 files 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.
- 5d ago First seen · 1,234 lines · 0 tokens per session scan A e6121ddb0986
monthly-review is a skill published in the GitHub repository natea/ExoMind (21 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 8,278 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 2026-09-03.
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