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 devinilabs/pro-skill --skill design-game-encountersgit clone --depth 1 https://github.com/devinilabs/pro-skillWrote 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/devinilabs/pro-skill/design-game-encounters)<a href="https://agentmods.dev/skills/devinilabs/pro-skill/design-game-encounters"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/design-game-encounters.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 | $0.00046 | $0.00198 |
| Opus 5 | $0.00023 | $0.00099 |
| Sonnet 5 | $0.00009 | $0.00040 |
| Haiku 4.5 | $0.00005 | $0.00020 |
Grade A, and why
design-game-encounters 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
100% identical to design-game-encounters — 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.
What it actually says
Design Game Encounters
Design encounters as decisions, not actor counts.
Compose
Define objective, available space, enemy roles, spawn timing, hazards, player resources, exits, failure recovery, and reward. Add one pressure source at a time; require each archetype to create a distinct response.
Keep it fair
Protect readable paths, telegraphs, camera sight lines, and recovery windows. Cap simultaneous committed attackers and avoid offscreen damage, unavoidable chains, or encounter resets that duplicate rewards.
Validate
Create deterministic starts for low resources, each wave, boss phase, victory, and death/retry. Test desktop and mobile at the real camera distance, then adjust composition from observed decisions rather than raw completion time.
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 · 21 lines · 46 tokens per session scan A 0cb2da5d4fbc
design-game-encounters is a skill published in the GitHub repository devinilabs/pro-skill (23 stars, last pushed 26d ago), licensed MIT. It adds 46 tokens to every session and 198 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to design-game-encounters, differing in 0 lines, and is treated as a copy.
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