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 commands/equity-rigor/us-equity-research/researchgit clone --depth 1 https://github.com/equity-rigor/us-equity-researchWrote 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/commands/equity-rigor/us-equity-research/research)<a href="https://agentmods.dev/commands/equity-rigor/us-equity-research/research"><img src="https://agentmods.dev/badge/commands/equity-rigor/us-equity-research/research.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 5.1 | $0.00044 | $0.00530 |
| Opus 5 | $0.00022 | $0.00265 |
| Sonnet 5 | $0.00009 | $0.00106 |
| Haiku 4.5 | $0.00004 | $0.00053 |
Grade A, and why
research scanned grade A with 1 finding 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 6d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Bash(curl *) What it actually says
Load the us-equity-research skill and begin Phase 0 fundamental research on the ticker provided.
If a ticker is provided as the first argument, use it. Otherwise ask the user which US-listed name to research (NYSE/Nasdaq/AMEX/OTC tickers, plus ADRs via 20-F/6-K).
Default mode: EDGAR-only + free-aggregator data (Yahoo Finance, StockAnalysis.com, WSJ Markets). Premium data hooks (Visible Alpha, Capital IQ, AlphaSense, Bloomberg) gate behind explicit user opt-in.
Required Phase 0 minimum per D9: at least 12 WebSearch+WebFetch calls across industry context, SEC filings (10-K/10-Q/8-K/DEF 14A/20-F as relevant), regulatory desk (FTC/DOJ/state AGs/EU CMA/BIS/OFAC/CFIUS/sector regulators per D12), positioning desk (13F clusters, Form 4 net, short interest, options skew, ETF passive %, sell-side distribution, activist 13D), forensic accounting (ASC 606/842/718, non-GAAP/GAAP delta, SBC treatment, goodwill, auditor history, restatement history), and a sector-appropriate baseline valuation per D8.
Output Phase 0 to outputs/{TICKER}_structured.json + outputs/{TICKER}_Research_Document_{date}.md. Do NOT shape into IC memo or scenario framework — that is the us-equity-ic-rigor skill's job.
If the user's request implies an IC memo (memo / opinion letter / PM red-team / score-band language), chain into us-equity-ic-rigor immediately after Phase 0 completes. Otherwise stop at Phase 0.
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.
- 6d ago First seen · 36 lines · 44 tokens per session scan A b914dfaab765
research is a command published in the GitHub repository equity-rigor/us-equity-research (4 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 530 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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