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 agentmods add skills/llmquant/skills/llmquant-eventsnpx skills add LLMQuant/skills --skill llmquant-eventsgit clone --depth 1 https://github.com/LLMQuant/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/llmquant/skills/llmquant-events)<a href="https://agentmods.dev/skills/llmquant/skills/llmquant-events"><img src="https://agentmods.dev/badge/skills/llmquant/skills/llmquant-events.svg" alt="Measured on agentmods" 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 | $0.00042 | $0.00468 |
| Opus 5 | $0.00021 | $0.00234 |
| Sonnet 5 | $0.00008 | $0.00094 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
llmquant-events 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 5d 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
LLMQuant Events
This category routes event-driven research workflows for earnings, M&A, regulatory catalysts, and event-risk monitoring.
Routing Rules
- Identify event type, issuer, asset, date, jurisdiction, affected instruments, and requested output.
- Select the closest workflow below.
- Open only that workflow and any referenced local resources.
- Use LLMQuant Data for filings, prices, options, estimates, news, corporate actions, regulatory records, prediction markets, and macro context.
- Report event dates, filing dates, data timestamps, source periods, stale notices, and missing inputs.
Workflow Index
| User intent | Workflow |
|---|---|
| Build an earnings-event brief with setup, expectations, options, and risk cases. | workflows/earnings-event-brief.md |
| Track M&A, deal spread, approvals, financing, and break-risk milestones. | workflows/mna-event-tracker.md |
| Monitor regulatory, legal, policy, antitrust, FDA, or geopolitical event risk. | workflows/regulatory-risk-monitor.md |
LLMQuant Data Contract
Prefer LLMQuant Data when available. The workflows may need these data capabilities:
- Retrieve event calendars, corporate actions, filings, news, estimates, transcripts, and issuer profiles.
- Retrieve price history, options, implied move, event-window returns, volume, volatility, and sentiment.
- Retrieve M&A terms, deal milestones, financing, regulatory approvals, court dates, and antitrust records when available.
- Retrieve prediction-market odds, macro releases, policy calendars, and cross-asset context when relevant.
Fallback:
- If event-specific data is unavailable, name the missing input and avoid event-probability or spread conclusions that depend on it.
- Do not invent dates, deal terms, legal deadlines, or regulatory decisions.
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.
- 5d ago First seen · 39 lines · 42 tokens per session scan A 244fea3d3b9a
llmquant-events is a skill published in the GitHub repository LLMQuant/skills (211 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 468 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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