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 Frontal-so/outbound-skills --skill content-engagementgit clone --depth 1 https://github.com/Frontal-so/outbound-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/frontal-so/outbound-skills/content-engagement)<a href="https://agentmods.dev/skills/frontal-so/outbound-skills/content-engagement"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/content-engagement/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/frontal-so/outbound-skills/content-engagement"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/content-engagement.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 | $0.00075 | $0.01155 |
| Opus 5 | $0.00037 | $0.00577 |
| Sonnet 5 | $0.00015 | $0.00231 |
| Haiku 4.5 | $0.00007 | $0.00115 |
Grade A, and why
content-engagement 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 11d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Engagement Signals
Content engagement signals span INBOUND and POSTBOUND categories in the taxonomy. They reveal brand awareness, category interest, and research activity. LinkedIn engagement = 30 points (Tier 2). Webinar attendance = 25 points. These are warm prospects who already know you.
Reference Files
- Read
{SKILL_BASE}/resources/signal-taxonomy.mdfor INBOUND triggers 1-30 (content, events, social engagement) - Read
{SKILL_BASE}/resources/examples/signal-campaigns/gtm-plays.mdfor Play 11 (Inbound Followers)
Content Signal Types
First-Party (Your Content)
| Signal | Points | Category |
|---|---|---|
| Webinar attendance | 25 | INBOUND - Category interest |
| Case study download | 35 | INBOUND - Research phase |
| Newsletter subscriber | 15 | INBOUND - Brand awareness |
| 3+ blog posts read | 20 | INBOUND - Early research |
| Email click-through | 15 | POSTBOUND - Active interest |
| Aggressive email opens | 10 | POSTBOUND - Monitoring |
Second-Party (Social Engagement)
| Signal | Points | Category |
|---|---|---|
| Commented on your LinkedIn post | 35 | POSTBOUND - Active engagement |
| Liked your LinkedIn post | 25 | POSTBOUND - Passive engagement |
| Followed company LinkedIn page | 15 | INBOUND - Brand awareness |
| Community engagement (Slack/Discord) | 30 | INBOUND - Active interest |
| Engaged with employee personal page | 20 | POSTBOUND - Network awareness |
Trigify Setup (LinkedIn Engagement Tracking)
- Create account at trigify.io
- Add LinkedIn URLs to monitor (your company page, executive profiles, competitor pages)
- Configure signal types: Engagement, Social Signals, Job Changes
- Set up Clay webhook:
- Clay: Create table with webhook source, copy webhook URL
- Trigify: Select data sources, enter Clay webhook URL, test connection
- Trigify sends automatically on each new engagement event
What Trigify Captures
- Person: name, title, company, LinkedIn URL
- Engagement: post URL, type (like/comment), comment text
- Company data: size, industry, domain
- Signal type: engagement, job change, viral post
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.
- 11d ago First seen · 107 lines · 75 tokens per session scan A 830c23c6b314
content-engagement is a skill published in the GitHub repository Frontal-so/outbound-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 75 tokens to every session and 1,155 once invoked, about $0.0004 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 2026-08-31.
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