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 ohong/agent-skills --skill spring-cleaninggit clone --depth 1 https://github.com/ohong/agent-skillsWrote 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/ohong/agent-skills/spring-cleaning)<a href="https://agentmods.dev/skills/ohong/agent-skills/spring-cleaning"><img src="https://agentmods.dev/badge/skills/ohong/agent-skills/spring-cleaning.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 5.1 | $0.00119 | $0.02552 |
| Opus 5 | $0.00060 | $0.01276 |
| Sonnet 5 | $0.00024 | $0.00510 |
| Haiku 4.5 | $0.00012 | $0.00255 |
Grade C, and why
spring-cleaning scanned grade C with 1 finding 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 7d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf ~/.Trash/* How it starts
The opening of the file, as written. The whole thing — 315 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spring Cleaning — Mac Disk Space Cleanup
A skill for generating a safe, prioritized, step-by-step runbook to free up
local disk space on a Mac. Before recommending offloading or deletion, confirm
the user's backup, cloud-sync, and external-storage setup. Useful optional tools
include DaisyDisk, ncdu, dust, fdupes, and brew.
Step 1 — Get a Storage Snapshot
Before generating the runbook, the agent needs a storage report. Accept any of the following (in order of detail/usefulness):
| Report Type | How to Get It | Detail Level |
|---|---|---|
dust output |
dust -d 4 /Users/<name> 2>/dev/null |
✅ Good |
| DaisyDisk screenshot | Scan Macintosh HD, share screenshot | ✅ Good |
ncdu filtered output |
See command below | ✅✅ Best |
| System Settings > Storage screenshot | Built-in macOS storage view | ⚠️ Low (ask for more) |
ncdu filtered command (recommend this if user hasn't run anything yet):
ncdu / -o /tmp/ncdu_out.json 2>/dev/null && python3 << 'EOF'
import json
with open('/tmp/ncdu_out.json') as f:
data = json.load(f)
def walk(node, path='', threshold=200*1024*1024):
if isinstance(node, list):
info = node[0]
name = info.get('name', '')
full = f"{path}/{name}".replace('//', '/')
size = info.get('asize', 0)
if size > threshold:
print(f"{size // 1024 // 1024}MB\t{full}")
for child in node[1:]:
walk(child, full, threshold)
elif isinstance(node, dict):
name = node.get('name', '')
full = f"{path}/{name}".replace('//', '/')
size = node.get('asize', 0)
if size > threshold:
print(f"{size // 1024 // 1024}MB\t{full}")
root = data[2]
walk(root, threshold=200*1024*1024)
EOF
If the user only provides a high-level screenshot (e.g. macOS Storage view
showing category totals), ask for a DaisyDisk scan or dust output before
generating the runbook — the category-level view isn't granular enough to write
safe, targeted commands.
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.
- 7d ago First seen · 315 lines · 119 tokens per session scan C c237efc912b6
spring-cleaning is a skill published in the GitHub repository ohong/agent-skills (3 stars, last pushed 7d ago), licensed MIT. It adds 119 tokens to every session and 2,552 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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