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 prof-little-bear/cc-equity-research --skill idea-generationgit clone --depth 1 https://github.com/prof-little-bear/cc-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/skills/prof-little-bear/cc-equity-research/idea-generation)<a href="https://agentmods.dev/skills/prof-little-bear/cc-equity-research/idea-generation"><img src="https://agentmods.dev/badge/skills/prof-little-bear/cc-equity-research/idea-generation/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/prof-little-bear/cc-equity-research/idea-generation"><img src="https://agentmods.dev/badge/skills/prof-little-bear/cc-equity-research/idea-generation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.00894 |
| Opus 5 | $0.00000 | $0.00447 |
| Sonnet 5 | $0.00000 | $0.00179 |
| Haiku 4.5 | $0.00000 | $0.00089 |
Grade A, and why
idea-generation 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 10d 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.
This is a copy
95% identical to idea-generation — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Idea Generation
description: Systematic stock screening and investment idea sourcing. Combines quantitative screens, thematic research, and pattern recognition to surface new long and short ideas. Use when looking for new ideas, running screens, or conducting thematic sweeps. Triggers on "idea generation", "stock screen", "find ideas", "what looks interesting", "screen for", "new ideas", or "pitch me something".
Workflow
Step 1: Define Search Criteria
Ask the user for parameters:
- Direction: Long ideas, short ideas, or both
- Market cap: Large, mid, small, micro
- Sector: Specific sector or cross-sector
- Style: Value, growth, quality, special situation, event-driven
- Geography: US, international, global
- Theme: Any specific thematic angle (AI, reshoring, aging demographics, etc.)
Step 2: Quantitative Screens
Run screens based on the style:
Value Screen
- P/E below sector median
- EV/EBITDA below historical average
- Free cash flow yield >5%
- Price/book below 1.5x
- Insider buying in last 90 days
- Dividend yield above market average
Growth Screen
- Revenue growth >15% YoY
- Earnings growth >20% YoY
- Revenue acceleration (growth rate increasing)
- Expanding margins
- High return on invested capital (>15%)
- Strong net retention (>110% for SaaS)
Quality Screen
- Consistent revenue growth (5+ years)
- Stable or expanding margins
- ROE >15%
- Low debt/equity
- High free cash flow conversion
- Insider ownership >5%
Short Screen
- Declining revenue or decelerating growth
- Margin compression
- Rising receivables / inventory vs. sales
- Insider selling
- Valuation premium to peers without justification
- High short interest with deteriorating fundamentals
- Accounting red flags (auditor changes, restatements)
Special Situation Screen
- Recent IPOs / SPACs with lockup expirations
- Spin-offs in last 12 months
- Companies emerging from restructuring
- Activist involvement
- Management changes at underperforming companies
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.
- 10d ago First seen · 112 lines · 0 tokens per session scan A 83a3dec62c4b
idea-generation is a skill published in the GitHub repository prof-little-bear/cc-equity-research (88 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 894 tokens. A static security scan graded it A with 0 findings. It is 95% identical to idea-generation, differing in 7 lines, and is treated as a copy.
Other skills, from other repositories
equity-research
Full-stack equity research report generator built on the Anamnesis Pattern (cross-session institutional memory + scheduled adversarial review). Trigger when the user wants to analyze a company, generate an equity research report, fundamental analysis, or stock investment research. Works with a company name (web…
octagon-analyst-master
Route broad company, sector, valuation, filings, transcript, and market data questions into the right Octagon workflow. Use when the user wants full-scope investment research or when multiple Octagon skills may be needed.
prediction-markets-analysis
Generate Kalshi prediction market research reports or fetch structured event history. Use when the user mentions Kalshi, prediction markets, market probability, expected return, or event history.
analyst-estimates
Retrieve analyst financial estimates including revenue and EPS projections with ranges and coverage. Use when analyzing forward expectations, consensus assumptions, or valuation inputs for a public company.
earnings-call-analysis
Analyze earnings call transcripts for guidance, management commentary, analyst concerns, and strategic signals. Use when the user asks about earnings calls, transcript takeaways, management tone, or future guidance.
sec-10k-analysis
Analyze 10-K annual filings to extract business model, financial priorities, risk factors, segments, and notable changes. Use when the user asks about 10-Ks, annual filings, SEC risk factors, or filing-based due diligence.