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 alexclowe/awesome-copilot-cowork-plugins --skill social-analyticsgit clone --depth 1 https://github.com/alexclowe/awesome-copilot-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/skills/alexclowe/awesome-copilot-cowork-plugins/social-analytics)<a href="https://agentmods.dev/skills/alexclowe/awesome-copilot-cowork-plugins/social-analytics"><img src="https://agentmods.dev/badge/skills/alexclowe/awesome-copilot-cowork-plugins/social-analytics/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/alexclowe/awesome-copilot-cowork-plugins/social-analytics"><img src="https://agentmods.dev/badge/skills/alexclowe/awesome-copilot-cowork-plugins/social-analytics.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 | $0.00015 | $0.01077 |
| Opus 5 | $0.00008 | $0.00539 |
| Sonnet 5 | $0.00003 | $0.00215 |
| Haiku 4.5 | $0.00002 | $0.00108 |
Grade A, and why
social-analytics 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 9d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You understand social media analytics deeply and can translate raw metrics into actionable business insights. When the user is working on reporting, analytics, or performance analysis tasks, apply this knowledge automatically.
Core metrics knowledge
Engagement metrics by platform:
- Instagram engagement rate: (Likes + Comments + Saves + Shares) / Followers x 100. Industry average: 1-3% for most accounts. Above 3% is strong; above 6% is exceptional.
- LinkedIn engagement rate: (Reactions + Comments + Shares) / Impressions x 100. Average: 2-4% for company pages; higher for personal profiles.
- TikTok engagement rate: (Likes + Comments + Shares + Saves) / Views x 100. Average: 3-9% depending on account size. Smaller accounts tend to have higher rates.
- X/Twitter engagement rate: (Likes + Retweets + Replies + Clicks) / Impressions x 100. Average: 0.5-1.5%.
- Facebook engagement rate: (Reactions + Comments + Shares) / Reach x 100. Average: 0.5-1.5% for pages.
Reach vs Impressions:
- Reach: unique accounts that saw the content (one person = one reach count)
- Impressions: total views including repeat views from the same account
- Frequency = Impressions / Reach — how many times each person saw the content on average
Audience growth metrics:
- Net new followers = New followers - Unfollows
- Growth rate = Net new followers / Total followers x 100
- Organic vs paid follower growth — distinguish between the two in reporting
Conversion metrics:
- Click-through rate (CTR): Clicks / Impressions x 100
- Conversion rate: Conversions / Clicks x 100
- Cost per click (CPC), cost per thousand impressions (CPM), cost per acquisition (CPA) for paid campaigns
- Return on ad spend (ROAS): Revenue generated / Ad spend
Attribution and tracking:
- UTM parameters: source, medium, campaign, term, content — use these to track social traffic in web analytics
- First-touch vs last-touch vs multi-touch attribution models
- Assisted conversions — social may not be the last click but contributed to the journey
- Track UTM-tagged links per platform and campaign for accurate attribution
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.
- 9d ago First seen · 83 lines · 15 tokens per session scan A 4e37f302035a
social-analytics is a skill published in the GitHub repository alexclowe/awesome-copilot-cowork-plugins (17 stars, last pushed 1mo ago), licensed MIT. It adds 15 tokens to every session and 1,077 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 2026-09-03.
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