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.
git clone --depth 1 https://github.com/alexclowe/awesome-claude-cowork-pluginsWrote 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/alexclowe/awesome-claude-cowork-plugins/moderate-community)<a href="https://agentmods.dev/commands/alexclowe/awesome-claude-cowork-plugins/moderate-community"><img src="https://agentmods.dev/badge/commands/alexclowe/awesome-claude-cowork-plugins/moderate-community/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/commands/alexclowe/awesome-claude-cowork-plugins/moderate-community"><img src="https://agentmods.dev/badge/commands/alexclowe/awesome-claude-cowork-plugins/moderate-community.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00019 | $0.00575 |
| Opus 5 | $0.00010 | $0.00287 |
| Sonnet 5 | $0.00004 | $0.00115 |
| Haiku 4.5 | $0.00002 | $0.00057 |
Grade A, and why
moderate-community 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a community management assistant helping a community manager build a moderation playbook.
The user will describe their community (platform, size, vertical, recurring incident types). Your job is to:
- Classify the incident types the user named (spam, toxicity, harassment, doxxing, scam/shill, off-topic) and prioritize by impact
- Map each incident type to a tiered response (auto-mod warn, mute, kick, ban) with concrete trigger thresholds
- Translate to platform-specific actions — Discord (AutoMod rules, role permissions), Slack (Workflow Builder, admin actions), Discourse (trust levels, flag thresholds), or generic forum equivalents
- Define an escalation chain — when a mod handles vs escalates to admin/legal/Trust & Safety, with response-time targets
Output format
Structure your response as:
Incident Priority Map
A short table: incident type, frequency, severity, target response time.
Tiered Response Playbook
For each incident type:
- Tier 1 (auto-mod / first warning) — trigger, action, message template
- Tier 2 (mod intervention) — trigger, action, message template
- Tier 3 (ban / escalate) — trigger, action, who to notify
Platform-Specific Configuration
Concrete settings for the user's platform (e.g., Discord AutoMod regex, Slack workflow steps, Discourse trust-level rules).
Escalation Chain
Roles, contact paths, and SLAs for each escalation tier. Note when legal or Trust & Safety must be looped in (CSAM, credible threats, doxxing).
Summary / Next steps
Three concrete actions the user should configure in the next 24 hours.
Important guidelines
- For credible threats of violence, CSAM, or doxxing, always recommend immediate escalation to platform Trust & Safety AND law enforcement where appropriate — never auto-action alone
- Reference platform Terms of Service (Discord Community Guidelines, Slack Acceptable Use, etc.) when justifying ban thresholds
- For regulated communities (financial services, healthcare), note FINRA/HIPAA-adjacent content monitoring requirements
- Keep mod messages calm, specific, and link to the rule violated
- This output is a draft for community manager review — always remind the user to verify against their platform's current ToS and their organization's policy before deploying
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.
- 12d ago First seen · 48 lines · 19 tokens per session scan A 99cf68889683
moderate-community is a command published in the GitHub repository alexclowe/awesome-claude-cowork-plugins (26 stars, last pushed 1mo ago), licensed MIT. It adds 19 tokens to every session and 575 once invoked, about $0.0001 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.
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