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 tupe12334/instinct --skill pareto-analysisgit clone --depth 1 https://github.com/tupe12334/instinctWrote 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/tupe12334/instinct/pareto-analysis)<a href="https://agentmods.dev/skills/tupe12334/instinct/pareto-analysis"><img src="https://agentmods.dev/badge/skills/tupe12334/instinct/pareto-analysis.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 | $0.00034 | $0.02781 |
| Opus 5 | $0.00017 | $0.01391 |
| Sonnet 5 | $0.00007 | $0.00556 |
| Haiku 4.5 | $0.00003 | $0.00278 |
Grade A, and why
pareto-analysis 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 7d 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pareto Analysis
Overview
The Pareto Principle — named after economist Vilfredo Pareto — observes that roughly 80% of effects come from 20% of causes. Pareto Analysis turns this observation into a structured method: quantify contributions, rank them, identify the vital few, and concentrate effort there rather than spreading it thin across the trivial many.
Cumulative %
of effect
100% | ···············
80% |············· ·
| · ·
| · ·
| · ·
| ·· ··
0% +──────────────────────────────────────────▶
20% 50% 80% 100%
% of causes
◀── vital few ──▶◀────── trivial many ──────▶
The inflection point — where the cumulative curve bends — marks the boundary between your vital few and the rest.
Core Concepts
Causes vs. Effects
A cause is any discrete category: a customer segment, a bug type, a product SKU, a failure mode, a cost center. An effect is the measurable outcome attributed to each cause: revenue, defect count, churn rate, cost. You must pick one effect metric before starting — mixing metrics distorts the ranking.
Cumulative Frequency
Each cause's contribution is expressed as a percentage of the total effect, then accumulated in descending order. The cumulative column reveals the crossover point — the fewest causes that explain the most effect.
Vital Few vs. Trivial Many
The vital few are the top causes that together account for ~80% of the effect. The trivial many account for the remaining ~20% but are far more numerous. Effort belongs on the vital few; the trivial many rarely justify proportional investment.
The 80/20 Ratio Is a Guideline
The real split may be 70/30 or 90/10. Do not force the data to hit 80%. Look for the natural inflection in the cumulative curve — that is your signal, not the number 80.
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.
- 7d ago First seen · 155 lines · 34 tokens per session scan A d5d40be8b8db
pareto-analysis is a skill published in the GitHub repository tupe12334/instinct (1 stars, last pushed 21d ago), licensed MIT. It adds 34 tokens to every session and 2,781 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 2026-08-31.
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