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 staskh/trading_skills --skill earnings-calendargit clone --depth 1 https://github.com/staskh/trading_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/staskh/trading_skills/earnings-calendar)<a href="https://agentmods.dev/skills/staskh/trading_skills/earnings-calendar"><img src="https://agentmods.dev/badge/skills/staskh/trading_skills/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/staskh/trading_skills/earnings-calendar"><img src="https://agentmods.dev/badge/skills/staskh/trading_skills/earnings-calendar.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 | $0.00040 | $0.00430 |
| Opus 5 | $0.00020 | $0.00215 |
| Sonnet 5 | $0.00008 | $0.00086 |
| Haiku 4.5 | $0.00004 | $0.00043 |
Grade A, and why
earnings-calendar 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 11d 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 Calendar
Retrieve upcoming earnings dates for stocks.
Instructions
Note: If
uvis not installed orpyproject.tomlis not found, replaceuv run pythonwithpythonin all commands below.
uv run python scripts/earnings.py SYMBOLS
Arguments
SYMBOLS- Ticker symbol or comma-separated list (e.g.,AAPLorAAPL,MSFT,GOOGL,NVDA)
Output
Single symbol returns:
symbol- Ticker symbolearnings_date- Next earnings date (YYYY-MM-DD)timing- "BMO" (Before Market Open), "AMC" (After Market Close), or nulleps_estimate- Consensus EPS estimate, or null if unavailable
Multiple symbols returns:
results- Array of earnings info, sorted by date (soonest first)
Examples
# Single symbol
uv run python scripts/earnings.py NVDA
# Multiple symbols (sorted by date)
uv run python scripts/earnings.py AAPL,MSFT,GOOGL,NVDA,META
# Portfolio earnings calendar
uv run python scripts/earnings.py CAT,GOOG,HOOD,IWM,NVDA,PLTR,QQQ,UNH
Use Cases
- Check when positions have upcoming earnings risk
- Plan trades around earnings announcements
- Build an earnings calendar for watchlist
Dependencies
pandasyfinance
Timezone
All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.
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.
- 11d ago First seen · 61 lines · 40 tokens per session scan A 3e0f53f1f0b6
earnings-calendar is a skill published in the GitHub repository staskh/trading_skills (363 stars, last pushed 10d ago), licensed MIT. It adds 40 tokens to every session and 430 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 2026-08-30.
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