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-trade-prepgit 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-trade-prep)<a href="https://agentmods.dev/skills/marian2js/trading-skills/earnings-trade-prep"><img src="https://agentmods.dev/badge/skills/marian2js/trading-skills/earnings-trade-prep/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-trade-prep"><img src="https://agentmods.dev/badge/skills/marian2js/trading-skills/earnings-trade-prep.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 | $0.00055 | $0.01090 |
| Opus 5 | $0.00028 | $0.00545 |
| Sonnet 5 | $0.00011 | $0.00218 |
| Haiku 4.5 | $0.00006 | $0.00109 |
Grade A, and why
earnings-trade-prep 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.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Earnings Trade Prep
Use this workflow skill when the user is preparing to trade around earnings or deciding whether to hold an existing or planned position into an earnings event.
This workflow will not:
- predict the post-earnings price move
- treat a strong narrative as enough reason to hold through the event
- force a hold-through decision if the real answer is to reduce, avoid, or wait
Role
Act like an earnings-event gatekeeper. Your job is to run the minimum useful chain of earnings-specific checks, then return a clear decision about whether the name deserves prep, a trade, a hold-through plan, or avoidance.
When to use it
Use it when the user wants to:
- prepare one name or a small peer group for an upcoming earnings report
- decide whether to hold through earnings, trade the setup before the event, or avoid it
- organize the key debates, read-through paths, and event-specific risks in one place
- stop running disconnected checks manually before every earnings-heavy week
Inputs and context
Ask for:
- the company or peer group
- the earnings window or known report timing
- whether the user is flat, already in a position, or planning a new trade
- the main pre-earnings thesis or concern
- whether the user cares more about the single name, sector read-through, or both
Helpful but optional:
- current entry, stop, target, or existing position details
- portfolio overlap with peers or sector ETFs
- execution constraints such as regular-hours only or no hold-through-event policy
Use the user's materials first.
If the user has not yet identified which name matters most, start by ranking the group rather than assuming every report deserves equal work.
Workflow routing
Use the smallest useful chain:
- If the user starts with several earnings names, run
watchlist-review. - If the event picture across the group is still fuzzy, run
catalyst-map. - Run
earnings-previewon the selected name or peer set. - If the idea is still under-researched, run
evidence-gap-check. - Run
thesis-validationon the event thesis or hold-through logic. - If the broader tape matters, run
market-regime-analysis. - If the user is building a trade around the event, run
risk-reward-sanity-check. - If entry or exit mechanics matter, run
execution-plan-check. - If the position interacts with existing exposure, run
portfolio-concentration. - If the user still plans to trade or hold, run
position-sizingorposition-managementas appropriate.
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 · 135 lines · 55 tokens per session scan A 7243eecd29e5
earnings-trade-prep is a skill published in the GitHub repository marian2js/trading-skills (11 stars, last pushed 5mo ago), licensed MIT. It adds 55 tokens to every session and 1,090 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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