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 eddiebelaval/squire --skill engagement-optimizergit clone --depth 1 https://github.com/eddiebelaval/squireWrote 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/eddiebelaval/squire/engagement-optimizer)<a href="https://agentmods.dev/skills/eddiebelaval/squire/engagement-optimizer"><img src="https://agentmods.dev/badge/skills/eddiebelaval/squire/engagement-optimizer.svg" alt="Measured on agentmods" 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 | $0.00759 |
| Opus 5 | $0.00008 | $0.00380 |
| Sonnet 5 | $0.00003 | $0.00152 |
| Haiku 4.5 | $0.00002 | $0.00076 |
Grade A, and why
Engagement Optimizer 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 4d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engagement Optimizer
Optimize social media engagement through comment strategies and DM automation
When to Use This Skill
Use this skill when you need to:
- Improve business operations and strategy
- Make data-driven business decisions
- Optimize processes and outcomes
Not recommended for:
- Tasks requiring creative design work
- technical coding
Quick Reference
| Action | Command/Trigger |
|---|---|
| Create engagement optimizer | engagement optimization |
| Review and optimize | review engagement optimizer |
| Get best practices | engagement optimizer best practices |
Core Workflows
Workflow 1: Initial Engagement Optimizer Creation
Goal: Create a high-quality engagement optimizer from scratch
Steps:
- Discovery - Understand requirements and objectives
- Planning - Develop strategy and approach
- Execution - Implement the plan
- Review - Evaluate results and iterate
- Optimization - Refine based on feedback
Workflow 2: Advanced Engagement Optimizer Optimization
Goal: Refine and optimize existing engagement optimizer for better results
Steps:
- Research - Gather relevant information
- Analysis - Evaluate options and approaches
- Decision - Choose the best path forward
- Implementation - Execute with precision
- Measurement - Track success metrics
Best Practices
-
Start with Clear Objectives Define what success looks like before beginning work.
-
Follow Industry Standards Leverage proven frameworks and best practices in business.
-
Iterate Based on Feedback Continuously improve based on results and user input.
-
Document Your Process Keep track of decisions and outcomes for future reference.
-
Focus on Quality Prioritize excellence over speed, especially in early iterations.
Checklist
Before considering your work complete:
- Objectives clearly defined and understood
- Research and discovery phase completed
- Strategy or plan documented
- Implementation matches requirements
- Quality standards met
- Stakeholders informed and aligned
- Results measured against goals
- Documentation updated
- Feedback collected
- Next steps identified
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.
- 4d ago First seen · 128 lines · 15 tokens per session scan A 5e0c2de022a2
Engagement Optimizer is a skill published in the GitHub repository eddiebelaval/squire (21 stars, last pushed 22d ago), licensed MIT. It adds 15 tokens to every session and 759 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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