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 VoDaiLocz/kilo-kit-mcp --skill scale-gamegit clone --depth 1 https://github.com/VoDaiLocz/kilo-kit-mcpWrote 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/vodailocz/kilo-kit-mcp/scale-game)<a href="https://agentmods.dev/skills/vodailocz/kilo-kit-mcp/scale-game"><img src="https://agentmods.dev/badge/skills/vodailocz/kilo-kit-mcp/scale-game/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/vodailocz/kilo-kit-mcp/scale-game"><img src="https://agentmods.dev/badge/skills/vodailocz/kilo-kit-mcp/scale-game.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 | $0.00027 | $0.00529 |
| Opus 5 | $0.00014 | $0.00264 |
| Sonnet 5 | $0.00005 | $0.00106 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
Scale Game 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.
This is a copy
100% identical to Scale Game — 0 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.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scale Game
Overview
Test your approach at extreme scales to find what breaks and what surprisingly survives.
Core principle: Extremes expose fundamental truths hidden at normal scales.
Quick Reference
| Scale Dimension | Test At Extremes | What It Reveals |
|---|---|---|
| Volume | 1 item vs 1B items | Algorithmic complexity limits |
| Speed | Instant vs 1 year | Async requirements, caching needs |
| Users | 1 user vs 1B users | Concurrency issues, resource limits |
| Duration | Milliseconds vs years | Memory leaks, state growth |
| Failure rate | Never fails vs always fails | Error handling adequacy |
Process
- Pick dimension - What could vary extremely?
- Test minimum - What if this was 1000x smaller/faster/fewer?
- Test maximum - What if this was 1000x bigger/slower/more?
- Note what breaks - Where do limits appear?
- Note what survives - What's fundamentally sound?
Examples
Example 1: Error Handling
Normal scale: "Handle errors when they occur" works fine At 1B scale: Error volume overwhelms logging, crashes system Reveals: Need to make errors impossible (type systems) or expect them (chaos engineering)
Example 2: Synchronous APIs
Normal scale: Direct function calls work At global scale: Network latency makes synchronous calls unusable Reveals: Async/messaging becomes survival requirement, not optimization
Example 3: In-Memory State
Normal duration: Works for hours/days At years: Memory grows unbounded, eventual crash Reveals: Need persistence or periodic cleanup, can't rely on memory
Red Flags You Need This
- "It works in dev" (but will it work in production?)
- No idea where limits are
- "Should scale fine" (without testing)
- Surprised by production behavior
Remember
- Extremes reveal fundamentals
- What works at one scale fails at another
- Test both directions (bigger AND smaller)
- Use insights to validate architecture early
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 · 64 lines · 27 tokens per session scan A 43373c54188b
Scale Game is a skill published in the GitHub repository VoDaiLocz/kilo-kit-mcp (26 stars, last pushed yesterday), licensed Apache-2.0. It adds 27 tokens to every session and 529 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to Scale Game, differing in 0 lines, and is treated as a copy.
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