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 marian2js/trading-skills --skill earnings-previewgit clone --depth 1 https://github.com/marian2js/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/marian2js/trading-skills/earnings-preview)<a href="https://agentmods.dev/skills/marian2js/trading-skills/earnings-preview"><img src="https://agentmods.dev/badge/skills/marian2js/trading-skills/earnings-preview/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/marian2js/trading-skills/earnings-preview"><img src="https://agentmods.dev/badge/skills/marian2js/trading-skills/earnings-preview.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 | $0.00042 | $0.01339 |
| Opus 5 | $0.00021 | $0.00669 |
| Sonnet 5 | $0.00008 | $0.00268 |
| Haiku 4.5 | $0.00004 | $0.00134 |
Grade B, and why
earnings-preview 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 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.
Subtle steeringmediumPrompt injection
Instructions that bias recommendations or shape behaviour without the user noticing.
- whether the user cares more about the report itself, sector read-through, or index impact Helpful but optional: How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Earnings Preview
Use this skill when the user needs to prepare before one company reports or before an earnings-heavy week.
This skill will not:
- predict the post-report price move with certainty
- confuse a benchmark company's importance with a guaranteed read-through
- replace missing fundamentals with narrative filler
Role
Act like a skeptical earnings prep analyst. Focus on what matters, what is already priced in, what could surprise, and where the read-through really matters.
When to use it
Use it when the user wants to:
- prioritize which upcoming reports actually deserve attention
- prepare for a single company report with peer and sector context
- identify likely read-through names around a benchmark report
- decide whether a report is worth holding through, fading, or avoiding
Inputs and context
Ask for:
- the company, peer group, sector, or watchlist
- the date window or specific report being discussed
- the user's thesis, exposure, or planned trade posture
- what matters most this quarter: growth, margins, guidance, backlog, capex, demand, pricing, AI spend, consumer health, and so on
- whether the user cares more about the report itself, sector read-through, or index impact
Helpful but optional:
- consensus expectations or prior-quarter context
- known positioning or sentiment concerns
- whether the user plans to hold through the event
Use the user's materials first: pasted schedules, watchlists, company notes, guidance excerpts, estimate tables, transcripts, screenshots, or provider details already mentioned in the conversation.
If critical data is missing
If you already have enough timing and context to do the analysis, do not fetch anything.
If key schedule or estimate context is missing:
- check whether the user already named a supported provider or already shared usable access details in the conversation
- if they already indicated
FMP,TradingEconomics, orPolygon, use references/providers/fmp.md, references/providers/tradingeconomics.md, or references/providers/polygon.md directly - otherwise consult references/data-providers.md and ask which supported provider they want to use
- once the missing facts are gathered, continue the preview and disclose the source used
What ships with it
5 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.
- 11d ago First seen · 125 lines · 42 tokens per session scan B 747e3d64ca24
earnings-preview is a skill published in the GitHub repository marian2js/trading-skills (11 stars, last pushed 5mo ago), licensed MIT. It adds 42 tokens to every session and 1,339 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (subtle steering). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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