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 defeat-beta/defeatbeta-api --skill defeatbeta-earnings-analysisgit clone --depth 1 https://github.com/defeat-beta/defeatbeta-apiWrote 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/defeat-beta/defeatbeta-api/defeatbeta-earnings-analysis)<a href="https://agentmods.dev/skills/defeat-beta/defeatbeta-api/defeatbeta-earnings-analysis"><img src="https://agentmods.dev/badge/skills/defeat-beta/defeatbeta-api/defeatbeta-earnings-analysis/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/defeat-beta/defeatbeta-api/defeatbeta-earnings-analysis"><img src="https://agentmods.dev/badge/skills/defeat-beta/defeatbeta-api/defeatbeta-earnings-analysis.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 | $0.00112 | $0.05525 |
| Opus 5 | $0.00056 | $0.02763 |
| Sonnet 5 | $0.00022 | $0.01105 |
| Haiku 4.5 | $0.00011 | $0.00553 |
Grade A, and why
defeatbeta-earnings-analysis 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 — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Equity Research Earnings Update
Create professional EARNINGS UPDATE REPORTS analyzing quarterly results for companies already under coverage, following institutional standards (JPMorgan, Goldman Sachs, Morgan Stanley format).
Key Characteristics:
- Length: 8-12 pages
- Word Count: 3,000-5,000 words
- Tables: 1-3 summary tables (NOT comprehensive)
- Figures: 8-12 charts
- Audience: Clients already familiar with the company
- Focus: What's NEW — beat/miss, updated estimates, thesis impact
- Font: Times New Roman throughout (unless user specifies otherwise)
When to Use
Use when the user requests:
- "Create an earnings update for [Company] Q3 2024"
- "Analyze [Company]'s quarterly results"
- "Post-earnings report for [Company]"
- "Q1/Q2/Q3/Q4 update for [Company]"
Do NOT use if:
- User requests "initiation report" → Use different skill
- User requests "flash note" or "quick take" → Different format
- Company is not already covered → Need initiation first
Critical Requirements
1. Language Matching
- Match the user's language for all user-facing output, including the DOCX report, delivery summary, replies, visible reasoning notes, assumptions, methodology explanations, and clarification questions
- If the user mixes languages, use the language that dominates the user's request unless the user explicitly specifies the report language
- Keep company names, tickers, financial terms, source names, accounting labels, and quoted source text in their original language when translation would reduce precision
- Do not expose hidden chain-of-thought; provide concise visible rationale, assumptions, and methodology in the user's language when useful
- If the report language differs from the source language, preserve source citations, MCP tool names, ticker symbols, and financial labels accurately
2. Focus
- Focus on what's NEW from this quarter — don't rehash company background
- Assume reader has seen the prior coverage (initiation report or prior earnings update on this name)
What ships with it
3 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.
- 12d ago First seen · 379 lines · 112 tokens per session scan A b2e34070dbf4
defeatbeta-earnings-analysis is a skill published in the GitHub repository defeat-beta/defeatbeta-api (746 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 112 tokens to every session and 5,525 once invoked, about $0.0006 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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