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 nerdai/llm-agents-from-scratch --skill hailstone-sequencegit clone --depth 1 https://github.com/nerdai/llm-agents-from-scratchWrote 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/nerdai/llm-agents-from-scratch/hailstone-sequence)<a href="https://agentmods.dev/skills/nerdai/llm-agents-from-scratch/hailstone-sequence"><img src="https://agentmods.dev/badge/skills/nerdai/llm-agents-from-scratch/hailstone-sequence.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 | $0.00032 | $0.00363 |
| Opus 5 | $0.00016 | $0.00181 |
| Sonnet 5 | $0.00006 | $0.00073 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
hailstone-sequence 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 8d 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
91% identical to stop-at-one — 8 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.
What it actually says
Hailstone Sequence
Compute the full Hailstone (Collatz) sequence from a starting number down to 1
using the next_number tool.
Arguments
The user must provide a starting number (a positive integer greater than 1).
If no starting number is given, ask the user before proceeding.
Steps
1. Initialize
Set the current number x to the starting number provided by the user.
Begin tracking the sequence as a list: [x].
2. Call the tool
Call next_number with the current value of x.
next_number(x=<current_number>)
STOP and WAIT for the tool result before continuing.
3. Record the result
Append the returned value to the sequence list.
Set x to the returned value.
4. Check termination
- If
x == 1, proceed to Step 5. - Otherwise, go back to Step 2.
Important rules:
- NEVER fabricate or simulate tool call results.
- NEVER make multiple tool calls in a single response.
- ALWAYS wait for the actual tool response before deciding next steps.
5. Report the result
Print the complete sequence from start to finish, for example:
6 → 3 → 10 → 5 → 16 → 8 → 4 → 2 → 1
Also report:
- Starting number
- Total steps taken (number of tool calls made)
- Maximum value reached in the sequence
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.
- 8d ago First seen · 63 lines · 32 tokens per session scan A 15ae62064e66
hailstone-sequence is a skill published in the GitHub repository nerdai/llm-agents-from-scratch (185 stars, last pushed yesterday), licensed Apache-2.0. It adds 32 tokens to every session and 363 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to stop-at-one, differing in 8 lines, and is treated as a copy.
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