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 cookjohn/teammcp --skill wechat-send-imagegit clone --depth 1 https://github.com/cookjohn/teammcpWrote 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/cookjohn/teammcp/wechat-send-image)<a href="https://agentmods.dev/skills/cookjohn/teammcp/wechat-send-image"><img src="https://agentmods.dev/badge/skills/cookjohn/teammcp/wechat-send-image.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 | $0.00031 | $0.00413 |
| Opus 5 | $0.00015 | $0.00206 |
| Sonnet 5 | $0.00006 | $0.00083 |
| Haiku 4.5 | $0.00003 | $0.00041 |
Grade B, and why
wechat-send-image scanned grade B 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
fetch('http://localhost:3100/api/wechat/send-file', { method: 'POST', What it actually says
Send Image to WeChat
Send an image file to WeChat. The image will be displayed inline in the WeChat conversation.
Arguments
$ARGUMENTS contains the image file path. If not provided, look for recent screenshots or ask the user.
Steps
1. Resolve Image Path
If $ARGUMENTS is provided, use it directly. Otherwise:
- Check for recent screenshots on the Desktop:
ls -t ~/Desktop/ScreenShot_* | head -5 - Ask the user which image to send
2. Validate Image
Use the Bash tool to run: ls -la "$ARGUMENTS"
Supported formats: jpg, jpeg, png, gif, bmp, webp
3. Send Image
Use the Bash tool to run:
node -e "
fetch('http://localhost:3100/api/wechat/send-file', {
method: 'POST',
headers: { 'Content-Type': 'application/json', 'Authorization': 'Bearer $TEAMMCP_KEY' },
body: JSON.stringify({ file_path: '$ARGUMENTS' })
}).then(r=>r.json()).then(d => {
if (d.ok) console.log('Image sent:', d.fileName, '(' + d.size + ' bytes)');
else console.error('Failed:', d.error);
});
"
4. Report Result
Confirm the image was sent successfully.
Technical Details
- Images are encrypted with AES-128-ECB before upload
- Uploaded to WeChat CDN (novac2c.cdn.weixin.qq.com)
- Sent as
image_itemwithencrypt_type: 1andmid_size(ciphertext size) - WeChat displays the image inline in the conversation
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 · 57 lines · 31 tokens per session scan B e6b2efd32f0a
wechat-send-image is a skill published in the GitHub repository cookjohn/teammcp (53 stars, last pushed 2mo ago), licensed MIT. It adds 31 tokens to every session and 413 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (sends data to an external url). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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