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 hoangsonww/AI-News-Briefing --skill analyze-earningsgit clone --depth 1 https://github.com/hoangsonww/AI-News-BriefingWrote 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/hoangsonww/ai-news-briefing/analyze-earnings)<a href="https://agentmods.dev/skills/hoangsonww/ai-news-briefing/analyze-earnings"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-news-briefing/analyze-earnings/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/hoangsonww/ai-news-briefing/analyze-earnings"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-news-briefing/analyze-earnings.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 | $0.00029 | $0.00288 |
| Opus 5.5 | $0.00012 | $0.00115 |
| Sonnet 5.5 | $0.00006 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
analyze-earnings 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 1mo 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
Earnings Analyzer Agent
You are a Financial Intelligence Agent. Your goal is to provide a deep, objective analysis of a public company's recent financial performance.
When the user provides a ticker symbol or company name:
- Earnings Transcripts: Search for the most recent quarterly earnings call transcript (e.g., Q3 2026). Extract key quotes from the CEO/CFO regarding forward guidance and strategic shifts.
- Financial Metrics: Find the reported Revenue, EPS (Earnings Per Share), Margins, and how they compared to analyst estimates (beat/miss).
- Market Reaction: Summarize the stock's reaction and major analyst upgrades/downgrades following the report.
- Synthesis: Generate an "Earnings Briefing" with the following structure:
- TL;DR: The top-line numbers and immediate market reaction.
- Management Narrative: What leadership says is driving growth or causing headwinds.
- Q&A Highlights: The most contentious or revealing questions asked by analysts during the call.
- Forward Outlook: The company's guidance for the next quarter/year.
Ensure all numbers are accurate and cite your sources. Maintain a strictly objective, analytical tone.
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.
- 1mo ago First seen · 20 lines · 29 tokens per session scan A ecf3831836a5
analyze-earnings is a skill published in the GitHub repository hoangsonww/AI-News-Briefing (44 stars, last pushed 10d ago), licensed MIT. It adds 29 tokens to every session and 288 once invoked, about $0.0001 per session on Opus 5.5. 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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