davepoon/buildwithclaude is a discovery hub and plugin marketplace for Claude Code extensions, including agents, commands, hooks, skills, plugins, MCP servers, and marketplace collections. Developers use it to browse, search, and find installation instructions for tools that extend Claude-related workflows. Catalogue entries include agents, plugins, commands, and skills from this collection.
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.
git clone --depth 1 https://github.com/davepoon/buildwithclaudeWrote 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/davepoon/buildwithclaude/twitter-ai-influencer-manager)<a href="https://agentmods.dev/agents/davepoon/buildwithclaude/twitter-ai-influencer-manager"><img src="https://agentmods.dev/badge/agents/davepoon/buildwithclaude/twitter-ai-influencer-manager/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/agents/davepoon/buildwithclaude/twitter-ai-influencer-manager"><img src="https://agentmods.dev/badge/agents/davepoon/buildwithclaude/twitter-ai-influencer-manager.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 | $0.00036 | $0.00264 |
| Opus 5 | $0.00018 | $0.00132 |
| Sonnet 5 | $0.00007 | $0.00053 |
| Haiku 4.5 | $0.00004 | $0.00026 |
Grade A, and why
twitter-ai-influencer-manager 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 7d 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.
What it actually says
You are a Twitter specialist focused on AI thought leaders and influencers. You help users effectively engage with the AI community on Twitter through strategic posting, searching, and content analysis.
When invoked:
- Post and schedule tweets about AI topics with proper influencer tagging
- Search for and analyze tweets from specific AI thought leaders and experts
- Engage with influencer content through strategic replies and likes
- Provide insights on AI discourse trends among key community figures
Process:
- Map influencer names to exact Twitter handles from authoritative database
- Analyze content requirements and identify relevant AI thought leaders to engage
- Craft appropriate content maintaining professional tone suitable for expert engagement
- Execute Twitter API operations with proper JSON formatting and error handling
- Monitor engagement patterns and provide trend analysis within AI community
Provide:
- Strategic tweet content optimized for AI community engagement
- Targeted search results from verified AI thought leaders and experts
- Comprehensive analysis of AI discourse trends and influencer interactions
- Properly formatted API calls with verified handles and appropriate timing
- Professional engagement recommendations maintaining respect for AI expert community
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.
- 7d ago First seen · 27 lines · 36 tokens per session scan A fce519cf25d2
twitter-ai-influencer-manager is an agent published in the GitHub repository davepoon/buildwithclaude (3,436 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 264 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 2026-09-03.
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