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 skills/arcadi4/nerdy/sorting-and-order-statisticsnpx skills add Arcadi4/nerdy --skill sorting-and-order-statisticsgit clone --depth 1 https://github.com/Arcadi4/nerdyWrote 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/arcadi4/nerdy/sorting-and-order-statistics)<a href="https://agentmods.dev/skills/arcadi4/nerdy/sorting-and-order-statistics"><img src="https://agentmods.dev/badge/skills/arcadi4/nerdy/sorting-and-order-statistics.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 | $0.00049 | $0.02913 |
| Opus 5 | $0.00024 | $0.01456 |
| Sonnet 5 | $0.00010 | $0.00583 |
| Haiku 4.5 | $0.00005 | $0.00291 |
Grade A, and why
sorting-and-order-statistics 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 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.
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 — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sorting and Order Statistics
Overview
Use sorting and selection as engineering tools, not reflexes. The core move is to identify the exact order information required, then choose the weakest ordering primitive that satisfies it under the real key, stability, memory, and adversary constraints.
Shared CLRS Conventions
Follow the parent clrs skill for mathematical formatting, formula-free headings, direct polished answers, and CLRS-wide answer style.
When to Use
- You need to sort records, select a percentile, maintain top-k, merge sorted streams, or implement a priority queue.
- A prompt involves heaps, heapsort, quicksort, counting sort, radix sort, bucket sort, medians, quantiles, or ith order statistics.
- A comparison-sort lower bound seems relevant, or a proposed linear-time sort depends on integer keys, digits, or distribution assumptions.
- An implementation must preserve satellite data, stability, handles, index maps, or large-payload locality.
Do not use this skill merely because output should appear sorted in a UI. Use the platform's ordinary sort unless algorithm choice, asymptotics, stability, or data-structure behavior matters.
First Decision: How Much Order Do You Need?
| Need | Prefer | Why |
|---|---|---|
| General ordered records | Library sort, stable sort if ties matter | Production sorts are engineered for cache, duplicates, depth limits, and language semantics |
| Stable order by small dense integer key | Counting sort or radix sort | Beats comparison sorting only because key values can index counts or digits |
| Dynamic repeated min/max | Binary heap priority queue | Maintains partial order, not full sorted order |
| Merge k sorted streams | Min-heap of stream heads | Gives total cost based on k, not total stream count as a sort key |
| Single rank, median, percentile threshold | Selection or nth_element |
Full sorting pays for order you will discard |
| Top-k unsorted | Size-k heap or selection threshold | Choose by k size, streaming needs, and memory |
| Top-k sorted | Select threshold, partition top-k, then sort only k | Avoids sorting the cold majority |
| Worst-case linear rank guarantee | Median-of-medians SELECT | Usually a fallback or proof tool because constants are high |
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 · 185 lines · 49 tokens per session scan A a27805efdb44
sorting-and-order-statistics is a skill published in the GitHub repository Arcadi4/nerdy (7 stars, last pushed 4mo ago), licensed MIT. It adds 49 tokens to every session and 2,913 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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