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 nicepkg/ai-workflow --skill earnings-calendargit clone --depth 1 https://github.com/nicepkg/ai-workflowWrote 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/nicepkg/ai-workflow/earnings-calendar)<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/earnings-calendar"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/earnings-calendar/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/nicepkg/ai-workflow/earnings-calendar"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/earnings-calendar.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 | $0.00107 | $0.05704 |
| Opus 5.5 | $0.00043 | $0.02282 |
| Sonnet 5.5 | $0.00021 | $0.01141 |
| Haiku 4.5 | $0.00011 | $0.00570 |
Grade B, and why
earnings-calendar scanned grade B with 1 finding 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.
Asks the agent to reveal its instructionsmediumSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
2. "No, get free key" → Show instructions (3.2.1) This is a copy
100% identical to earnings-calendar — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 722 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Earnings Calendar
Overview
This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. It focuses on companies with significant market capitalization (mid-cap and above, over $2B) that are likely to impact market movements. The skill generates organized markdown reports showing which companies are reporting earnings over the next week, grouped by date and timing (before market open, after market close, or time not announced).
Key Features:
- Uses FMP API for reliable, structured earnings data
- Filters by market cap (>$2B) to focus on market-moving companies
- Includes EPS and revenue estimates
- Multi-environment support (CLI, Desktop, Web)
- Flexible API key management
- Organized by date, timing, and market cap
Prerequisites
FMP API Key
This skill requires a Financial Modeling Prep API key.
Get Free API Key:
- Visit: https://site.financialmodelingprep.com/developer/docs
- Sign up for free account
- Receive API key immediately
- Free tier: 250 API calls/day (sufficient for weekly earnings calendar)
API Key Setup by Environment:
Claude Code (CLI):
export FMP_API_KEY="your-api-key-here"
Claude Desktop: Set environment variable in system or configure MCP server.
Claude Web: API key will be requested during skill execution (stored only for current session).
Core Workflow
Step 1: Get Current Date and Calculate Target Week
CRITICAL: Always start by obtaining the accurate current date.
Retrieve the current date and time:
- Use system date/time to get today's date
- Note: "Today's date" is provided in the environment ( tag)
- Calculate the target week: Next 7 days from current date
Date Range Calculation:
Current Date: [e.g., November 2, 2025]
Target Week Start: [Current Date + 1 day, e.g., November 3, 2025]
Target Week End: [Current Date + 7 days, e.g., November 9, 2025]
Why This Matters:
- Earnings calendars are time-sensitive
- "Next week" must be calculated from the actual current date
- Provides accurate date range for API request
What ships with it
4 files 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.
- 1mo ago First seen · 722 lines · 107 tokens per session scan B 29873fb5a68c
earnings-calendar is a skill published in the GitHub repository nicepkg/ai-workflow (288 stars, last pushed 9mo ago), licensed MIT. It adds 107 tokens to every session and 5,704 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks the agent to reveal its instructions). It is 100% identical to earnings-calendar, differing in 0 lines, and is treated as a copy.
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