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 bolivian-peru/os-moda --skill predictive-resourcesgit clone --depth 1 https://github.com/bolivian-peru/os-modaWrote 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/bolivian-peru/os-moda/predictive-resources)<a href="https://agentmods.dev/skills/bolivian-peru/os-moda/predictive-resources"><img src="https://agentmods.dev/badge/skills/bolivian-peru/os-moda/predictive-resources/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/bolivian-peru/os-moda/predictive-resources"><img src="https://agentmods.dev/badge/skills/bolivian-peru/os-moda/predictive-resources.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.00776 |
| Opus 5 | $0.00016 | $0.00388 |
| Sonnet 5 | $0.00007 | $0.00155 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
predictive-resources 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Predictive Resource Exhaustion
Don't wait for things to break. Predict when they will and fix proactively.
teachd Trend Data
Before collecting your own data points, check teachd — it has been observing CPU, memory, and services every 30 seconds since boot:
teach_patterns({ type: "trend", min_confidence: 0.3 })
teach_observations({ source: "memory", limit: 100 })
teachd automatically detects monotonic memory increases over 6+ data points. If it has already flagged a trend, use that instead of re-deriving manually.
Disk Growth Analysis
Collect data points over time and project forward:
shell_exec({ command: "df -h --output=target,used,avail,pcent / /var /nix/store /tmp 2>/dev/null || df -h" })
Track in memory — store periodic snapshots:
memory_store({
summary: "Disk snapshot: / 38% used, /nix/store 12GB",
detail: "Full df output...",
category: "system.config",
tags: "disk,snapshot,predictive"
})
When you have 2+ data points, calculate growth rate:
- Growth per day = (current_used - previous_used) / days_between
- Days until 95% = (capacity * 0.95 - current_used) / growth_per_day
Thresholds & Alerts
| Metric | Warning | Critical | Action |
|---|---|---|---|
| Disk fills in < 7 days | Alert user | Auto-clean | nix-collect-garbage, logrotate |
| Memory avg > 80% for 1hr | Alert user | OOM risk | Identify top consumers |
| Swap usage growing | Monitor | > 50% used | Recommend more RAM or optimize |
| /nix/store > 30GB | Suggest cleanup | > 50GB | Auto-GC old generations |
Remediation (NixOS-native)
Disk: Nix garbage collection
shell_exec({ command: "nix-collect-garbage --delete-older-than 14d" })
Disk: Log rotation via NixOS config
Propose adding to configuration.nix:
services.journald.extraConfig = "SystemMaxUse=500M";
Memory: Identify and advise
shell_exec({ command: "ps aux --sort=-%mem | head -15" })
Don't kill processes without permission. Advise the user.
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 · 105 lines · 33 tokens per session scan A 39395461f6d8
predictive-resources is a skill published in the GitHub repository bolivian-peru/os-moda (117 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 776 once invoked, about $0.0002 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 2026-08-30.
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