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 frankxai/awesome-gamification-agent-skills --skill progression-system-auditorgit clone --depth 1 https://github.com/frankxai/awesome-gamification-agent-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/frankxai/awesome-gamification-agent-skills/progression-system-auditor)<a href="https://agentmods.dev/skills/frankxai/awesome-gamification-agent-skills/progression-system-auditor"><img src="https://agentmods.dev/badge/skills/frankxai/awesome-gamification-agent-skills/progression-system-auditor/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/frankxai/awesome-gamification-agent-skills/progression-system-auditor"><img src="https://agentmods.dev/badge/skills/frankxai/awesome-gamification-agent-skills/progression-system-auditor.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 | $0.00071 | $0.00286 |
| Opus 5 | $0.00036 | $0.00143 |
| Sonnet 5 | $0.00014 | $0.00057 |
| Haiku 4.5 | $0.00007 | $0.00029 |
Grade A, and why
progression-system-auditor 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.
What it actually says
Progression System Auditor
Use this skill to review a progression system before it becomes product infrastructure.
Audit Workflow
- Identify every rank, XP source, reward, and gate.
- Check whether each reward changes what the user or agent can do.
- Check whether XP has evidence.
- Check whether rank-up requires a Trial.
- Check for grind loops and repeated easy farming.
- Check for unsafe autonomy unlocks.
- Check privacy, IP, and stewardship boundaries.
- Produce repairs, not just criticism.
Red Flags
- XP for raw prompts, tokens, files, or time.
- One global level hiding actual strengths.
- Rank-up without a task fixture or eval.
- Rewards that only decorate a dashboard.
- Agent permissions granted as a prize.
- Public ledger exposing private memory.
- Lore names making platform rules unclear.
Output Shape
- Severity-ranked findings.
- Evidence and file references.
- Repair recommendation for each finding.
- Suggested Trial or gate.
- Residual risk.
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 · 39 lines · 71 tokens per session scan A 2247d5b15285
progression-system-auditor is a skill published in the GitHub repository frankxai/awesome-gamification-agent-skills (0 stars, last pushed 3d ago), licensed MIT. It adds 71 tokens to every session and 286 once invoked, about $0.0004 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 2026-09-01.
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