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 proyecto26/system-design-skills --skill scaling-evolutiongit clone --depth 1 https://github.com/proyecto26/system-design-skillsWrote 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/proyecto26/system-design-skills/scaling-evolution)<a href="https://agentmods.dev/skills/proyecto26/system-design-skills/scaling-evolution"><img src="https://agentmods.dev/badge/skills/proyecto26/system-design-skills/scaling-evolution.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 | $0.00147 | $0.02617 |
| Opus 5 | $0.00073 | $0.01308 |
| Sonnet 5 | $0.00029 | $0.00523 |
| Haiku 4.5 | $0.00015 | $0.00262 |
Grade A, and why
scaling-evolution 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.
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scaling Evolution
Grow a design one bottleneck at a time. A system that serves 1k users and one that serves 10M users are different architectures, but you do not jump between them — you walk a path where each step removes the current ceiling and exposes the next. Getting this wrong means either over-building day one (paying multi- region complexity for 1k users) or freezing when load doubles because the design was a memorized end-state, not a sequence of justified moves (GUIDE #7).
When to reach for this
A load increase is on the table ("what if traffic 10×?", "scale to millions"), the user asks where the bottleneck is or what breaks first, or a single-box design has outgrown one machine. Reach here to sequence the next two or three moves — never the whole roadmap at once.
When NOT to
Do not pre-build steps the numbers do not yet demand (YAGNI). Sharding, multi-region, and a message queue are late moves; proposing them for a system that fits on two boxes is the over-indexing this skill defends against. If the current load fits comfortably on a vertically-scaled box with a replica, stop — that is the cheapest design that meets the constraint, and it wins. Naming the next five tiers when only one is needed is a red flag, not foresight.
Clarify first
The path is driven entirely by numbers and constraints, so pin these down before
moving (most come from requirements-scoping and back-of-the-envelope):
- Current and target scale — today's QPS/data and the multiple you must hit (2×? 100×?). The multiple decides how many steps you take now.
- Read:write ratio — read-heavy systems scale with replicas + cache; write- heavy systems hit the master/storage ceiling and need sharding far sooner.
- Where it hurts now — is the symptom compute (CPU saturated), storage (DB/disk saturated), or network (bandwidth/connections)? Diagnose before adding.
- Consistency and staleness budget — replicas and multi-region trade freshness
for scale; if reads must be current, that constrains the path (→
consistency-coordination). - State — is anything pinned to a server (sessions, local files)? Stateful tiers block horizontal scaling.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 169 lines · 147 tokens per session scan A 892ad181e375
scaling-evolution is a skill published in the GitHub repository proyecto26/system-design-skills (69 stars, last pushed 3mo ago), licensed MIT. It adds 147 tokens to every session and 2,617 once invoked, about $0.0007 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 2026-08-30.
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