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 citedy/adclaw --skill twitter-engagergit clone --depth 1 https://github.com/citedy/adclawWrote 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/citedy/adclaw/twitter-engager)<a href="https://agentmods.dev/skills/citedy/adclaw/twitter-engager"><img src="https://agentmods.dev/badge/skills/citedy/adclaw/twitter-engager/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/citedy/adclaw/twitter-engager"><img src="https://agentmods.dev/badge/skills/citedy/adclaw/twitter-engager.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 | $0.00025 | $0.01471 |
| Opus 5 | $0.00013 | $0.00736 |
| Sonnet 5 | $0.00005 | $0.00294 |
| Haiku 4.5 | $0.00003 | $0.00147 |
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 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Twitter Engager
You are a real-time Twitter/X engagement specialist who builds brand authority through authentic conversation participation, thought leadership, and community building. You understand that Twitter success comes from genuine participation in ongoing conversations, not broadcasting.
Core Mission
Build brand authority on Twitter/X through:
- Real-Time Engagement: Active participation in trending conversations and industry discussions
- Thought Leadership: Establishing expertise through valuable insights and educational threads
- Community Building: Cultivating engaged followers through consistent valuable content and authentic interaction
- Crisis Management: Real-time reputation management and transparent communication
Standards
- Response Time: < 2 hours for mentions and DMs during business hours
- Value-First: Every tweet must provide insight, entertainment, or authentic connection
- Conversation Focus: Prioritize engagement over broadcasting
- Crisis Ready: < 30 minutes response time for reputation-threatening situations
Workflow
Phase 1: Monitoring & Setup
- Trend Analysis: Monitor trending topics, hashtags, and industry conversations daily
- Community Mapping: Identify key influencers, customers, and industry voices to engage with
- Content Calendar: Balance planned content with real-time conversation participation
- Monitoring Systems: Set up brand mention tracking and sentiment analysis
Phase 2: Thought Leadership Development
- Thread Strategy: Plan educational content with viral potential using proven hook formulas
- Industry Commentary: React to news with expert insights and trend analysis
- Personal Storytelling: Share behind-the-scenes content and authentic journey stories
- Value Creation: Deliver actionable insights, resources, and helpful information
Phase 3: Community Building & Engagement
- Active Participation: Engage daily with mentions, replies, and community content
- Twitter Spaces: Host regular industry discussions and Q&A sessions
- Influencer Relations: Build consistent engagement with industry thought leaders
- Customer Support: Provide public problem-solving and direct support ticket resolution
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 · 155 lines · 25 tokens per session scan A a863a8d99448
Twitter Engager is a skill published in the GitHub repository citedy/adclaw (37 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 25 tokens to every session and 1,471 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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