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 agentmods add commands/cloud-forest-analytics/evergreen/newslettergit clone --depth 1 https://github.com/Cloud-Forest-Analytics/evergreenWrote 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/cloud-forest-analytics/evergreen/newsletter)<a href="https://agentmods.dev/commands/cloud-forest-analytics/evergreen/newsletter"><img src="https://agentmods.dev/badge/commands/cloud-forest-analytics/evergreen/newsletter.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 | $0.00037 | $0.00197 |
| Opus 5 | $0.00018 | $0.00098 |
| Sonnet 5 | $0.00007 | $0.00039 |
| Haiku 4.5 | $0.00004 | $0.00020 |
Grade A, and why
newsletter 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 3d 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.
What it actually says
Run the weekly-seedling skill to produce this week's newsletter for THIS repo.
Arguments: $ARGUMENTS
- (none) — full run: infer the domain, research, editorial burn, render the self-contained HTML, file the GitHub issue, send the file to the operator.
--dry— research + editorialize only; print the digest and the Verdict Sheet, but do NOT write a file or open an issue.
Follow the weekly-seedling skill exactly: infer the repo's domain first, source from repos (not press releases), put every item through the default-cut editorial burn with an {ADOPT/BORROW/WATCH/SKIP} verdict, enforce the adopt cap, and verify every claim before print.
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.
- 3d ago First seen · 14 lines · 37 tokens per session scan A 2635263a2d64
newsletter is a command published in the GitHub repository Cloud-Forest-Analytics/evergreen (1 stars, last pushed 2mo ago), licensed MIT. It adds 37 tokens to every session and 197 once invoked, about $0.0002 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 2026-08-31.
Other commands, from other repositories
health
Scan all projects for stale research, forgotten ADRs, unresolved review conditions, orphaned artifacts, missing traceability, and version drift.
init
Install the formatters this repository needs, with every command visible before it runs.
brand-generate
Generate an on-brand document from a saved Brand Profile.
genshijin-compress
Markdown・テキストファイルを原始人形式へ安全圧縮.
save
Save this conversation as a new or existing reusable context.
standup
Show a daily standup summary with completed, in-progress, and blocked tasks across all active epics.