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 jeremylongworth-source/AgentSkills --skill game-content-designgit clone --depth 1 https://github.com/jeremylongworth-source/AgentSkillsWrote 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/jeremylongworth-source/agentskills/game-content-design)<a href="https://agentmods.dev/skills/jeremylongworth-source/agentskills/game-content-design"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/game-content-design/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/jeremylongworth-source/agentskills/game-content-design"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/game-content-design.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 | $0.00063 | $0.00711 |
| Opus 5 | $0.00032 | $0.00356 |
| Sonnet 5 | $0.00013 | $0.00142 |
| Haiku 4.5 | $0.00006 | $0.00071 |
Grade A, and why
game-content-design 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 7d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Game Content Design
Core Workflow
- Identify the genre, target audience, session length, platform, progression model, content budget, and intended player fantasy.
- Define the content's job: teach, test, reward, surprise, escalate, relax, branch, gate, reveal, or create mastery.
- Establish constraints before authoring: available mechanics, enemy roster, verbs, locations, assets, pacing target, difficulty range, and production limits.
- Think compositionally about content when useful: combine reusable mechanics, enemy capabilities, modifiers, objectives, rewards, and environmental constraints instead of inventing bespoke one-off content every time.
- Build content around player decisions. Avoid sequences that only ask the player to follow instructions unless the goal is onboarding or atmosphere.
- Use escalation deliberately: introduce, combine, twist, pressure, resolve. Track what the player has learned before asking for mastery.
- Specify rewards, failure recovery, replay value, and telemetry or playtest signals where relevant.
Content Types
- Levels: define route, landmarks, gates, loops, shortcuts, sightlines, encounter spaces, traversal tests, secrets, and reset/retry points.
- Quests and missions: define objective chain, motivation, stakes, optional branches, fail states, handoff points, reward logic, and world-state changes.
- Encounters: define enemy composition, terrain, timing, spawn rules, pressure pattern, counterplay, resource drain, and exit condition.
- Items and rewards: define acquisition source, rarity, power budget, tradeoffs, upgrade path, economy impact, and player-facing explanation.
- Progression: define unlock cadence, mastery curve, difficulty ramp, build diversity, catch-up mechanics, and anti-grind safeguards.
- Tutorials: teach one concept at a time, provide safe practice, then require use in a real context.
Compositional Content Design
Use modular content pieces when designing variants:
- Enemy variants can be composed from movement, attack, defense, perception, status, and reward capabilities.
- Encounters can be composed from terrain pressure, enemy roles, resource constraints, objective pressure, timing, and escape/retry rules.
- Items can be composed from stat changes, verbs, tradeoffs, proc effects, restrictions, rarity, and upgrade hooks.
- Levels can be composed from traversal tests, combat spaces, landmarks, gates, loops, secrets, and rest points.
- Quests can be composed from motivations, objectives, complications, choices, rewards, and world-state consequences.
What ships with it
2 files 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.
- 7d ago First seen · 55 lines · 63 tokens per session scan A c3de93341171
game-content-design is a skill published in the GitHub repository jeremylongworth-source/AgentSkills (1 stars, last pushed 9d ago), licensed MIT. It adds 63 tokens to every session and 711 once invoked, about $0.0003 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 2026-09-03.
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