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 sandbaseai/sandbase-skills --skill last30days-researchgit clone --depth 1 https://github.com/sandbaseai/sandbase-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/sandbaseai/sandbase-skills/last30days-research)<a href="https://agentmods.dev/skills/sandbaseai/sandbase-skills/last30days-research"><img src="https://agentmods.dev/badge/skills/sandbaseai/sandbase-skills/last30days-research/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/sandbaseai/sandbase-skills/last30days-research"><img src="https://agentmods.dev/badge/skills/sandbaseai/sandbase-skills/last30days-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.00500 |
| Opus 5 | $0.00029 | $0.00250 |
| Sonnet 5 | $0.00012 | $0.00100 |
| Haiku 4.5 | $0.00006 | $0.00050 |
Grade A, and why
last30days-research 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 12d 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
Last 30 Days Research
Comprehensive recent-history research across multiple platforms through SandBase. Aggregate the last 30 days of activity on a topic from Reddit, Twitter, YouTube, news, and web search. Read the API map before selecting a capability.
Call SandBase capabilities
For every selected tool, call sandbase_describe_tool first and use only arguments in its current input schema. Then call sandbase_call_tool with the exact tool_name.
Operating principles
- Cast a wide net: query at least 3-4 platforms for comprehensive coverage.
- Weight recency — more recent signals are more relevant.
- Note platform bias: Reddit skews technical, Twitter skews real-time, YouTube skews educational.
- Cross-reference findings for confidence scoring.
- Report timeline: when did mentions spike or change tone?
Workflow
1. Web and news
Use tavily_search with days: 30 and topic: "news" for news coverage.
Use google_news_bulk_articles for comprehensive news articles.
Use exa_search with date filters for high-quality web sources.
2. Social platforms
Use twitter_web_search_timeline for Twitter/X mentions and discussions.
Use reddit_app_dynamic_search for Reddit discussions.
Use youtube_web_v2_general_search for relevant YouTube content.
3. Synthesize timeline
Cluster findings by week, identify spikes, track sentiment changes.
Output
Return: timeline of activity, platform-by-platform summary, key events/milestones, sentiment trend, influencer involvement, and gaps/blind spots.
Example tasks
- "What's happened with [topic] in the last 30 days across the internet?"
- "Track [product launch] reception across all platforms over the past month."
- "How has discussion about [company] evolved on Twitter and Reddit recently?"
- "Find all significant mentions of [person] in the last 30 days."
- "What's the recent trend around [technology]? Combine news, social, and community data."
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 51 lines · 58 tokens per session scan A 1d46e27fae00
last30days-research is a skill published in the GitHub repository sandbaseai/sandbase-skills (151 stars, last pushed 3d ago), licensed Apache-2.0. It adds 58 tokens to every session and 500 once invoked, about $0.0003 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 2026-08-30.
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