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 Ootto-AI/claude-content-skills --skill community-engagement-plangit clone --depth 1 https://github.com/Ootto-AI/claude-content-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/ootto-ai/claude-content-skills/community-engagement-plan)<a href="https://agentmods.dev/skills/ootto-ai/claude-content-skills/community-engagement-plan"><img src="https://agentmods.dev/badge/skills/ootto-ai/claude-content-skills/community-engagement-plan/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/ootto-ai/claude-content-skills/community-engagement-plan"><img src="https://agentmods.dev/badge/skills/ootto-ai/claude-content-skills/community-engagement-plan.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 | $0.00111 | $0.00635 |
| Opus 5 | $0.00056 | $0.00318 |
| Sonnet 5 | $0.00022 | $0.00127 |
| Haiku 4.5 | $0.00011 | $0.00064 |
Grade A, and why
community-engagement-plan 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Community Engagement Plan
Set a useful participation standard: where the team can add value, what it can truthfully say, and when it should not speak.
1. Define the community and permission boundary
Ask which owned or external community is in scope, its rules, the team's legitimate role, the topic, and any moderator or brand constraints. Read supplied rules before proposing interaction. If the community does not welcome promotion or brand participation, do not design a workaround.
2. Identify contribution opportunities
Use real questions, recurring friction, useful resources, corrections, and support needs as evidence. Classify participation as answer, clarification, acknowledgement, escalation, or observation. Give priority to helping people complete a task, not inserting the brand into every thread.
3. Establish response boundaries and routing
Define approved facts, prohibited claims, tone, disclosure, escalation owners, response windows, and cases that require silence or human review. Route product bugs, safety concerns, account-specific issues, legal questions, and hostile interactions to the appropriate owner rather than improvising publicly.
4. Run a light learning loop
Set a small cadence to review unanswered questions, recurring themes, and useful contributions. Capture aggregate learning for social-listening. Measure quality through resolved questions, informed feedback, and community trust signals where available, not reply volume alone.
Hard rules
- Never automate unsolicited replies, direct messages, follows, or engagement.
- Do not misrepresent an employee, customer, or independent community member.
- Follow each community's rules and moderator direction; leave when asked.
- Do not reveal private account, customer, or support information in public conversation.
- Avoid argumentative pile-ons, engagement bait, and opportunistic promotion during sensitive events.
Failure modes
| Failure | Do this instead |
|---|---|
| The plan is "reply to everything" | Define situations where the team can add real value and where it should observe. |
| A public reply attempts to solve a private account issue | Acknowledge the issue and route through the approved support path. |
| Replies become repetitive promotion | Lead with the user's question, resource, or correction rather than the product. |
| Community rules are discovered after posting | Review rules and obtain required permission before engaging. |
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 · 46 lines · 111 tokens per session scan A 56512cbc9598
community-engagement-plan is a skill published in the GitHub repository Ootto-AI/claude-content-skills (30 stars, last pushed 20d ago), licensed MIT. It adds 111 tokens to every session and 635 once invoked, about $0.0006 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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