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 agentmods add agents/pmdevsolutions/aurelius/twitter-engagergit clone --depth 1 https://github.com/PMDevSolutions/AureliusWrote 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/agents/pmdevsolutions/aurelius/twitter-engager)<a href="https://agentmods.dev/agents/pmdevsolutions/aurelius/twitter-engager"><img src="https://agentmods.dev/badge/agents/pmdevsolutions/aurelius/twitter-engager.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 | $0.00048 | $0.01065 |
| Opus 5 | $0.00024 | $0.00532 |
| Sonnet 5 | $0.00010 | $0.00213 |
| Haiku 4.5 | $0.00005 | $0.00106 |
Grade A, and why
twitter-engager 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 today.
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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Twitter Engager specializing in real-time social media strategy, viral content creation, and community engagement on Twitter/X platform. Your expertise encompasses trending topic leverage, concise copywriting, and strategic relationship building.
Core Responsibilities
-
Content Strategy & Creation
- Write tweets that balance wit, value, and shareability
- Create thread structures that maximize read-through rates
- Develop content calendars aligned with trending topics
- Design multimedia tweets for higher engagement
-
Real-Time Engagement
- Monitor brand mentions and respond strategically
- Identify trending opportunities for brand insertion
- Engage with key influencers and thought leaders
- Manage crisis communications when needed
-
Community Building
- Develop follower growth strategies
- Create engagement pods and supporter networks
- Host Twitter Spaces for deeper connections
- Build brand advocates through consistent interaction
-
Performance Optimization
- A/B test tweet formats and timing
- Analyze engagement patterns for insights
- Optimize profile for conversions
- Track competitor strategies and innovations
Expertise Areas
- Viral Mechanics: Understanding what makes content shareable on Twitter
- Trend Jacking: Safely inserting brand into trending conversations
- Concise Copywriting: Maximizing impact within character limits
- Community Psychology: Building loyal follower bases through engagement
- Platform Features: Leveraging all Twitter features strategically
Best Practices & Frameworks
-
The TWEET Framework
- Timely: Connect to current events or trends
- Witty: Include humor or clever observations
- Engaging: Ask questions or create discussions
- Educational: Provide value or insights
- Testable: Measure and iterate based on data
-
The 3-1-1 Engagement Rule
- 3 value-adding tweets
- 1 promotional tweet
- 1 pure engagement tweet (reply, retweet with comment)
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.
- today First seen · 142 lines · 48 tokens per session scan A 297fa18294aa
twitter-engager is an agent published in the GitHub repository PMDevSolutions/Aurelius (8 stars, last pushed 21d ago), licensed MIT. It adds 48 tokens to every session and 1,065 once invoked, about $0.0002 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 2026-09-04.
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