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 research-bundlegit 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/research-bundle)<a href="https://agentmods.dev/skills/yennanliu/investskill/research-bundle"><img src="https://agentmods.dev/badge/skills/yennanliu/investskill/research-bundle/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/research-bundle"><img src="https://agentmods.dev/badge/skills/yennanliu/investskill/research-bundle.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 | $0.00031 | $0.01140 |
| Opus 5.5 | $0.00012 | $0.00456 |
| Sonnet 5.5 | $0.00006 | $0.00228 |
| Haiku 4.5 | $0.00003 | $0.00114 |
Grade A, and why
research-bundle 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 1mo 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Bundle
This skill has been unified into
full-report. Use/us-stock-analysis:full-reportwith a--depthflag instead:
| Old Usage | New Equivalent |
|---|---|
/research-bundle AAPL --quick |
/us-stock-analysis:full-report AAPL --depth quick |
/research-bundle AAPL |
/us-stock-analysis:full-report AAPL --depth standard |
/research-bundle AAPL (full) |
/us-stock-analysis:full-report AAPL --depth comprehensive |
The full-report skill absorbs everything research-bundle provided: the 5-phase framework, composite scoring weights, investment thesis narrative, conflict resolution rules, entry/exit strategy, and monitoring plan — plus HTML report output and configurable depth.
Composite Scoring Weights (Quick Reference)
Component Weight Sub-Score (0-10)
─────────────────────────────────────────────────────
Business Quality 25% [competitor + fundamental]
Valuation 25% [DCF + relative valuation]
Market Signals 20% [insider + institutional + earnings]
Technical Setup 15% [technical analysis timing]
Risk Profile 15% [short interest + options signals]
─────────────────────────────────────────────────────
COMPOSITE SCORE 100% X.X / 10
8.0–10.0 → Strong Buy | 6.5–7.9 → Buy
5.0–6.4 → Hold/Watch | 3.5–4.9 → Underweight
0.0–3.4 → Sell/Avoid
5-Phase Research Framework (reference)
The original research-bundle framework — now executed automatically by full-report:
Phase 1 — Business Foundation (competitor-analysis, sector-analysis) Assess economic moat width (Wide/Narrow/None), Porter's Five Forces, market share trajectory, and sector rotation positioning. Score: business quality 0–10.
Phase 2 — Valuation (dcf-valuation, stock-valuation) DCF intrinsic value across 3 scenarios + comparable company multiples (EV/EBITDA, P/E, P/S). Probability-weighted composite IV. Upside/downside to fair value.
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.
- 1mo ago First seen · 94 lines · 31 tokens per session scan A 7dcf1a1925a6
research-bundle is a skill published in the GitHub repository yennanliu/InvestSkill (250 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 1,140 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
dcf-model
Build a DCF valuation in Excel: FCF projections, WACC, terminal value, scenarios, sensitivity grids, reverse DCF. Triggers on build a DCF, what is it worth, intrinsic value, fair value, price target from cash flows.
comps-analysis
Comparable company analysis: peer set, operating metrics, valuation multiples, statistics and an implied value. Triggers on comps, trading comparables, how does it trade against peers, peer benchmarking, what multiple should it get.
company-profile
One-page company profile slide, four quadrants of overview, financial summary, share price chart and key facts. Also the compact profile paragraph when it has to sit inside a memo, a deck or a chat reply. Triggers on one-page profile, tear sheet, company snapshot, profile slide, quick profile of [company].
check-model
Audit a model somebody already built, and report on it without editing it: structure, formulas, integrity identities, source tie-out and reasonableness, ending in a routed issue log. Triggers on check my formulas, QA this spreadsheet, audit model, model review, something is off in my model, why does my balance sheet…
check-deck
QC an investment deck (a .pptx) before it circulates: number consistency, chart and narrative alignment, source coverage, language, then a circulation verdict. Triggers on check this deck, deck QC, review my presentation, is this ready to send, proofread the pitch book.
ui-design
Design-quality reference for financial-research visual output: typography, color, composition, and avoiding generic AI aesthetics.