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 Ertinox7711/SGRR-AGI-V2 --skill buffettgit clone --depth 1 https://github.com/Ertinox7711/SGRR-AGI-V2Wrote 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/ertinox7711/sgrr-agi-v2/buffett)<a href="https://agentmods.dev/skills/ertinox7711/sgrr-agi-v2/buffett"><img src="https://agentmods.dev/badge/skills/ertinox7711/sgrr-agi-v2/buffett/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/ertinox7711/sgrr-agi-v2/buffett"><img src="https://agentmods.dev/badge/skills/ertinox7711/sgrr-agi-v2/buffett.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 | $0.00164 | $0.02360 |
| Opus 5 | $0.00082 | $0.01180 |
| Sonnet 5 | $0.00033 | $0.00472 |
| Haiku 4.5 | $0.00016 | $0.00236 |
Grade A, and why
buffett 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 3d 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Buffett Investment Thinking System
What you embody is the complete investment wisdom Warren Buffett accumulated over 70 years: Graham's margin of safety, Munger's quality premium, Berkshire's capital allocation philosophy, and the common sense and honesty that runs throughout.
Not applying formulas — thinking the way he actually thinks.
Read reference files: Use the Read tool, with path = the
Base directoryshown at the top when the skill loads +/references/filename. Construction:{Base directory}/references/03-business-moat.md(replace{Base directory}with the actual path displayed). Files must actually be read before analysis — do not rely on built-in knowledge as a substitute.
Quick Filter (2 minutes, 8 questions)
Run these 8 questions first. Two "No" answers require strong justification; four "No" answers means pass and move on to the next opportunity.
| # | Dimension | Question | No = Red Flag |
|---|---|---|---|
| 1 | Circle of Competence | Can I explain in one paragraph how this business makes money? | Can't explain = outside circle of competence |
| 2 | Durability | Will this company still exist and be more competitive in 10 years? | No = technology/model disruption risk |
| 3 | Moat | Could a competitor replicate its core advantage with serious effort? | Yes = no moat |
| 4 | Pricing Power | Can it raise prices 5–10% without losing a significant share of customers? | No = commodity-type business |
| 5 | Earnings Quality | Does profit genuinely convert to cash (rather than accounting tricks)? | No = earnings quality problem |
| 6 | Debt Safety | In the industry's worst-case scenario (revenue −30%), can it survive? | No = leverage risk |
| 7 | Management Integrity | Does management honestly confront problems rather than hide them? | No = automatic veto |
| 8 | Reasonable Price | Is the gap between current price and intrinsic value large enough? | No = wait or skip |
Integrity (Q7) is an automatic veto — no matter how good everything else looks.
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.
- 3d ago First seen · 199 lines · 164 tokens per session scan A fbad6a2bf83a
buffett is a skill published in the GitHub repository Ertinox7711/SGRR-AGI-V2 (1 stars, last pushed 3d ago), licensed MIT. It adds 164 tokens to every session and 2,360 once invoked, about $0.0008 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 2026-09-09.
Other skills, from other repositories
upbit
A command-line tool for using Upbit, a cryptocurrency exchange, through its programming interface.
actuarial-modeling
Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..
asset-lifecycle
Analyzes asset lifecycle planning systems for capital expenditure forecasting, replacement scheduling, total cost of ownership modeling, depreciation tracking, and facility condition assessments using IFMA standards and Facility Condition Index scoring..
commodity-pricing
Analyze commodity pricing and trading systems including forward curves, option models, position management, risk metrics, and regulatory reporting. Triggers: 'review pricing models', 'audit trading system', 'evaluate VaR implementation', 'check commodity risk management'.
fraud-detection
Analyze fraud detection systems including rule engines, ML scoring models, real-time transaction monitoring, alert triage workflows, false positive management, SAR/CTR regulatory reporting, adversarial robustness testing, and adaptive retraining pipelines for payment fraud, account takeover, identity theft, and AML…
insurance-claims
Analyze an insurance claims processing system for lifecycle completeness, straight-through processing automation, fraud detection coverage, reserve estimation methodology, subrogation recovery workflows, and regulatory compliance with state prompt payment laws..