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/jaychempan/coding-with-beat/cwb-sleepgit clone --depth 1 https://github.com/jaychempan/coding-with-beatWrote 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/jaychempan/coding-with-beat/cwb-sleep)<a href="https://agentmods.dev/commands/jaychempan/coding-with-beat/cwb-sleep"><img src="https://agentmods.dev/badge/commands/jaychempan/coding-with-beat/cwb-sleep.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 | $0.00039 | $0.00276 |
| Opus 5 | $0.00019 | $0.00138 |
| Sonnet 5 | $0.00008 | $0.00055 |
| Haiku 4.5 | $0.00004 | $0.00028 |
Grade A, and why
cwb-sleep 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 4d 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
Sleep — 助眠 / 睡眠 / 白噪音
Run immediately — no analysis needed:
cwb smart_search "sleep music white noise ambient drone" > /tmp/cwb_sleep_1.txt 2>&1 &
cwb smart_search "lullaby soft piano rain sleep calm" > /tmp/cwb_sleep_2.txt 2>&1 &
cwb smart_search "meditation deep sleep binaural delta waves" > /tmp/cwb_sleep_3.txt 2>&1 &
wait
cat /tmp/cwb_sleep_1.txt
cat /tmp/cwb_sleep_2.txt
cat /tmp/cwb_sleep_3.txt
Display results in three groups with labels, renumber globally (1, 2, 3… across all groups):
🌙 Sleep Ambient (results from angle 1)
💤 Lullaby (results from angle 2)
🧘 Deep Sleep (results from angle 3)
End with: 喜欢哪首?说编号我来播。
Do NOT auto-play.
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.
- 4d ago First seen · 35 lines · 0 tokens per session scan A a68f5bc4d0f2
cwb-sleep is a command published in the GitHub repository jaychempan/coding-with-beat (114 stars, last pushed 2mo ago), licensed MIT. It adds 39 tokens to every session and 276 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 2026-08-30.
Other commands, from other repositories
pn-quieter
Reduce visual decoration — animations, colors, shadows, effects — without removing content. Use when there's too much visual noise. For content and feature reduction, use pn-distill.
org-map
Render a shareable org-map SVG (ORGMAP.svg) of this repo's org — roles, projects, captured lessons, token savings. Built to screenshot and post.
brainstorming
Facilitate interactive brainstorming sessions using diverse creative techniques and ideation methods. Use when the user says help me brainstorm or help me ideate.
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.