community-health-monitoring

community-health-monitoring is a skill for Claude Code, Codex from alexclowe/awesome-copilot-cowork-plugins. It costs 25 tokens per session (475 once invoked), scanned A, a copy of community-health-monitoring, MIT.

A set of guidance for monitoring the health of an online community, including participation, member retention, and signs that people may leave.

In plain words
What is it for?
Use it to examine active-member trends, message and reply activity, retention over time, churn signals, and possible re-engagement actions.
Why use it?
It gives community managers ways to spot declining activity or dissatisfaction before members disappear. It also suggests methods for encouraging members to stay engaged.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to examine active-member trends, message and reply activity, retention over time, churn signals, and possible re-engagement actions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alexclowe/awesome-copilot-cowork-plugins/community-health-monitoring
Install

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.

Any agent
npx skills add alexclowe/awesome-copilot-cowork-plugins --skill community-health-monitoring
Clone the repo
git clone --depth 1 https://github.com/alexclowe/awesome-copilot-cowork-plugins

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for community-health-monitoring

README.md
[![agentmods](https://agentmods.dev/badge/skills/alexclowe/awesome-copilot-cowork-plugins/community-health-monitoring/github.svg)](https://agentmods.dev/skills/alexclowe/awesome-copilot-cowork-plugins/community-health-monitoring)
Your own site
<a href="https://agentmods.dev/skills/alexclowe/awesome-copilot-cowork-plugins/community-health-monitoring"><img src="https://agentmods.dev/badge/skills/alexclowe/awesome-copilot-cowork-plugins/community-health-monitoring/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.

agentmods 80×15 button for community-health-monitoring

Your own site · 80×15
<a href="https://agentmods.dev/skills/alexclowe/awesome-copilot-cowork-plugins/community-health-monitoring"><img src="https://agentmods.dev/badge/skills/alexclowe/awesome-copilot-cowork-plugins/community-health-monitoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 475 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00025 $0.00475
Opus 5 $0.00013 $0.00237
Sonnet 5 $0.00005 $0.00095
Haiku 4.5 $0.00003 $0.00047

Measured 12d ago against content hash 104abaf3c7d7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

community-health-monitoring 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.

Origin

This is a copy

100% identical to community-health-monitoring — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

community-manager/skills/community-health-monitoring/SKILL.md · 44 lines

How it starts

The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You have deep expertise in community health monitoring. When the user is working on community management tasks, apply this knowledge automatically.

Core competencies

Engagement metrics:

  • Daily/weekly/monthly active members (DAM/WAM/MAM) and the L7/L28 ratio (sticky factor)
  • Message volume, thread depth, reply rate, and lurker-to-poster conversion
  • First-7-day activation rate (predicts long-term retention per CMX Hub and Feverbee research)
  • Cohort retention curves — Week 1, Month 1, Month 3 are the bend points to watch

Churn predictors:

  • Posting silence after a previously engaged member files a complaint
  • Drop-off from #general into a single niche channel (often precedes departure)
  • Negative or sarcastic reactions replacing previously positive ones
  • Membership status changes (role downgrades, payment failures in paid communities)

Retention levers:

  • Personalized re-engagement DM beats mass announcements ~3x in measured campaigns
  • Recognition mechanics (badges, shout-outs, member-of-the-month) sustain mid-tier members
  • Member-led sub-spaces (interest channels, local chapters) improve long-term retention more than mod-led programming

Reporting:

  • Map metrics to business outcomes (NRR for B2B customer communities, LTV for creator/paid communities, conversion for top-of-funnel communities)
  • Distinguish vanity metrics (raw member count) from health metrics (active member ratio, contribution diversity)

Communication style

When assisting with community health tasks:

  • Use platform-native terminology (Discord "boost", Slack "active members", Discourse "trust level")
  • Cite measurable signals over vibes — when the user says "things feel off," ask for the data slice
  • Flag confidence levels when sample sizes are small or sampling is biased
  • Always note that recommendations are drafts requiring community manager verification before use

Disclaimer

This plugin generates engagement and retention drafts for community manager review. It does not replace direct conversation with members or human judgment on individual situations.

Read the full file on GitHub · 44 lines

Changes

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.

  1. 12d ago First seen · 44 lines · 25 tokens per session scan A 104abaf3c7d7

Subscribe to this mod's changes

community-health-monitoring is a skill published in the GitHub repository alexclowe/awesome-copilot-cowork-plugins (17 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 475 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to community-health-monitoring, differing in 0 lines, and is treated as a copy.

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