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 OpenHands/extensions --skill slack-channel-monitorgit clone --depth 1 https://github.com/OpenHands/extensionsWrote 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/openhands/extensions/slack-channel-monitor)<a href="https://agentmods.dev/skills/openhands/extensions/slack-channel-monitor"><img src="https://agentmods.dev/badge/skills/openhands/extensions/slack-channel-monitor/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/openhands/extensions/slack-channel-monitor"><img src="https://agentmods.dev/badge/skills/openhands/extensions/slack-channel-monitor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Supply Chain · line 54 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Supply Chain · line 58 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Supply Chain · line 86 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Supply Chain · line 182 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Supply Chain · line 198 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Data Exfiltration · line 198 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 182 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00102 | $0.03429 |
| Opus 5.5 | $0.00041 | $0.01372 |
| Sonnet 5.5 | $0.00020 | $0.00686 |
| Haiku 4.5 | $0.00010 | $0.00343 |
Grade A, and why
slack-channel-monitor scanned grade A 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://slack.com/api/auth.test -H "Authorization: Bearer $SLACK_BOT_TOKEN" \ How it starts
The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Slack Channel Monitor
Create a cron automation that polls up to 10 Slack channels every minute.
Windows PowerShell equivalents for the setup, packaging, upload, and API-check shell snippets are in references/windows.md.
When a message containing the trigger phrase (default: @openhands) is
detected it:
- Adds a 👀 reaction to the triggering message.
- Opens an OpenHands conversation with the message and recent channel context.
- Posts a reply in the Slack thread with a link to the conversation.
On every subsequent run:
- New Slack thread replies are forwarded only when they contain the trigger phrase, so unrelated conversation in the thread is ignored.
- When the conversation finishes (or errors), the agent's final response is posted back to the Slack thread.
- Completed conversations stay in a short follow-up watch window, allowing triggered Slack replies to continue the same OpenHands conversation.
Runs on a local Agent Canvas (
dev:automationstack) and on OpenHands Cloud and Enterprise. On Cloud and Enterprise each conversation is started through the OpenHands API in a sandbox of its own, with the user's own settings, and the automation keeps its state in the automation service's KV store.
Prerequisites
Required secrets
Verify that at least one of the following secrets is set in OpenHands Settings → Secrets before proceeding:
| Secret name | Token type | Minimum scopes |
|---|---|---|
SLACK_BOT_TOKEN |
Bot (xoxb-…) |
channels:history, channels:read, reactions:write, chat:write |
SLACK_USER_TOKEN |
User (xoxp-…) |
Same as bot, plus search:read for multi-channel efficiency |
Check with:
# For bot token:
curl -s https://slack.com/api/auth.test -H "Authorization: Bearer $SLACK_BOT_TOKEN" \
| python3 -c "import json,sys; d=json.load(sys.stdin); print('ok' if d.get('ok') else d.get('error'))"
# For user token:
curl -s https://slack.com/api/auth.test -H "Authorization: Bearer $SLACK_USER_TOKEN" \
| python3 -c "import json,sys; d=json.load(sys.stdin); print('ok' if d.get('ok') else d.get('error'))"
What ships with it
9 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.
- today Changed · +12 lines aca5f53d025c
- 7d ago Changed · +3 lines 3b1d7a8db548
- 1mo ago First seen · 306 lines · 102 tokens per session scan A 2699798becdf
slack-channel-monitor is a skill published in the GitHub repository OpenHands/extensions (167 stars, last pushed today), licensed MIT. It adds 102 tokens to every session and 3,429 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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