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 yennanliu/InvestSkill --skill earnings-call-analysisgit clone --depth 1 https://github.com/yennanliu/InvestSkillWrote 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/yennanliu/investskill/earnings-call-analysis)<a href="https://agentmods.dev/skills/yennanliu/investskill/earnings-call-analysis"><img src="https://agentmods.dev/badge/skills/yennanliu/investskill/earnings-call-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/yennanliu/investskill/earnings-call-analysis"><img src="https://agentmods.dev/badge/skills/yennanliu/investskill/earnings-call-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 | $0.00013 | $0.03111 |
| Opus 5 | $0.00006 | $0.01555 |
| Sonnet 5 | $0.00003 | $0.00622 |
| Haiku 4.5 | $0.00001 | $0.00311 |
Grade A, and why
earnings-call-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 9d 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 — 438 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Earnings Call Analysis
⚠️ Data Verification — Do This Before Any Analysis
Before running any analysis, always retrieve the latest market data for the ticker:
- Fetch current price — use web search or ask the user for the live price, 52-week range, and market cap. Never assume a price from training data.
- Confirm key figures — recent earnings, revenue, key ratios (P/E, P/S, etc.) as applicable to this skill.
- State your data source — note where the numbers came from (e.g., "Google Finance, June 19 2026") at the top of the output.
- Flag stale data explicitly — if live data is unavailable, display this warning before proceeding:
⚠️ Live data unavailable. The following analysis uses training-data estimates which may be significantly out of date. Verify all prices and metrics before making any decisions.
Never silently substitute training-data estimates for current prices. When in doubt, ask the user to paste the latest quote.
Comprehensive analysis of earnings call transcripts to extract investment insights, management sentiment, strategic themes, and potential red flags.
Analysis Framework
1. Executive Summary Analysis
Extract and synthesize:
- Overall Sentiment: Bullish / Neutral / Bearish
- Key Takeaways: 3-5 most important points from the call
- Guidance Changes: Raised / Maintained / Lowered / Withdrawn
- Surprise Factors: Unexpected announcements or revelations
- Market-Moving Statements: Comments likely to impact stock price
2. Management Tone Assessment
Analyze management's communication style and confidence:
Confidence Indicators
- Use of definitive language ("will", "committed", "confident")
- Specific quantitative guidance with narrow ranges
- Proactive discussion of challenges with clear solutions
- Long-term vision and strategic clarity
Caution Indicators
- Hedging language ("may", "could", "hope", "expect")
- Wide guidance ranges or lack of specific targets
- Deflection of difficult questions
- Focus on short-term rather than strategic issues
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.
- 9d ago First seen · 438 lines · 13 tokens per session scan A a2ba56ac3e25
earnings-call-analysis is a skill published in the GitHub repository yennanliu/InvestSkill (205 stars, last pushed today), licensed MIT. It adds 13 tokens to every session and 3,111 once invoked, about $0.0001 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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chart-annotation
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