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 Lagunaswift/GameDevelopmentAudit --skill decision-flow-auditgit clone --depth 1 https://github.com/Lagunaswift/GameDevelopmentAuditWrote 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/lagunaswift/gamedevelopmentaudit/decision-flow-audit)<a href="https://agentmods.dev/skills/lagunaswift/gamedevelopmentaudit/decision-flow-audit"><img src="https://agentmods.dev/badge/skills/lagunaswift/gamedevelopmentaudit/decision-flow-audit/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/lagunaswift/gamedevelopmentaudit/decision-flow-audit"><img src="https://agentmods.dev/badge/skills/lagunaswift/gamedevelopmentaudit/decision-flow-audit.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 | $0.00123 | $0.01205 |
| Opus 5 | $0.00062 | $0.00602 |
| Sonnet 5 | $0.00025 | $0.00241 |
| Haiku 4.5 | $0.00012 | $0.00120 |
Grade A, and why
decision-flow-audit 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 10d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Decision Flow Audit
A decision is interesting when the player can partially predict its consequences: enough foresight to reason, enough uncertainty to make reasoning matter. Games fail on both sides, and they fail by feeding the player too little or too much information. This skill audits the thinking the game asks players to do.
Core concepts
Anticipation is where engagement lives. Players feel a game in the futures they imagine: threats forming, plans maturing, risks weighed. A game with no predictability offers nothing to imagine (pure dice); a game with total predictability offers nothing to decide (a solved puzzle). Tune systems so players can sketch the next few moments but not the exact outcome.
Predictability is a property of systems and AI. Enemies with readable tells, physics that behave consistently, and costs known in advance all buy anticipation. AI that acts arbitrarily destroys planning even when it is "smarter", because the player cannot model it. An AI that telegraphs is usually better game design than one that optimises.
Information balance has two failure modes. Starvation: the player lacks the facts needed to reason, so choices collapse into guessing. Glut: everything is visible and the best move is computable, so play becomes spreadsheet-reading, or the player drowns and disengages. Hide information with fog, hidden hands, randomised reveals, or fictional ambiguity; reveal it with tells, previews, and clear costs. Balance per decision, not globally.
Decision scope must fit the moment. Scope is how far a decision reaches: twitch reactions, tactical picks, strategic commitments. Real-time pressure suits small scopes; large scopes need time to think. Mismatches produce either panic (big decision, no time) or boredom (trivial decision, long pause).
Flow gaps and overflow. A flow gap is a stretch where the game asks nothing of the player's mind: dead travel, waiting on timers, foregone fights. Overflow is more simultaneous demands than attention can hold. Both eject the player from flow; audits should chart demand over time, not just average it.
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.
- 10d ago First seen · 45 lines · 123 tokens per session scan A b163ff2541ce
decision-flow-audit is a skill published in the GitHub repository Lagunaswift/GameDevelopmentAudit (5 stars, last pushed 1mo ago), licensed MIT. It adds 123 tokens to every session and 1,205 once invoked, about $0.0006 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 2026-08-31.
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