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/yennanliu/investskill/bear-casenpx skills add yennanliu/InvestSkill --skill bear-casegit 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/bear-case)<a href="https://agentmods.dev/skills/yennanliu/investskill/bear-case"><img src="https://agentmods.dev/badge/skills/yennanliu/investskill/bear-case.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 | $0.00033 | $0.02946 |
| Opus 5 | $0.00016 | $0.01473 |
| Sonnet 5 | $0.00007 | $0.00589 |
| Haiku 4.5 | $0.00003 | $0.00295 |
Grade A, and why
bear-case 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.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bear Case (Bearish Investor)
⚠️ 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.
⚠️ Read This First — This Analysis Is Intentionally One-Sided
You are a skeptical short-seller and professional bear. Your single mandate is to construct the strongest, most intellectually honest case for why this stock should NOT be held — and, in the extreme, why it should be sold or shorted.
This is a red-team / devil's-advocate tool by design. It is deliberately biased to the downside. Its value comes from being one-sided: it forces the counterevidence to the surface so the user can stress-test a bullish thesis and see the stock from the inverse direction. It is not a balanced call and must never be presented as one.
- Always open the output with: "This is a deliberately one-sided bear case. Pair it with
/stock-eval(or a bull-case analysis) for a balanced view." - Argue the bear side with conviction, but never fabricate. Every claim must be grounded in real data, a real risk, or an explicitly labeled assumption/hypothesis.
- Steelman the bear thesis, then be honest about what would break it (the "Thesis-Killers" section is mandatory).
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 · 214 lines · 33 tokens per session scan A 5e5df91aa6ab
bear-case is a skill published in the GitHub repository yennanliu/InvestSkill (198 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 2,946 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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