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 agentmods add skills/aaronnat23/disp8ch/model-usagenpx skills add aaronnat23/disp8ch --skill model-usagegit clone --depth 1 https://github.com/aaronnat23/disp8chWrote 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/aaronnat23/disp8ch/model-usage)<a href="https://agentmods.dev/skills/aaronnat23/disp8ch/model-usage"><img src="https://agentmods.dev/badge/skills/aaronnat23/disp8ch/model-usage.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 | $0.00000 | $0.00113 |
| Opus 5 | $0.00000 | $0.00056 |
| Sonnet 5 | $0.00000 | $0.00023 |
| Haiku 4.5 | $0.00000 | $0.00011 |
Grade A, and why
model-usage 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 4d 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
Model Usage
Explain model choice, provider tradeoffs, and cost or latency implications in practical terms.
Use when
- A user asks which model/provider should be used for a task.
- A workflow is slow, expensive, or mismatched to the job.
Workflow
- Identify the actual task shape: chat, coding, research, voice, or batch execution.
- Compare quality, speed, and setup friction.
- Prefer the simplest provider that satisfies the job.
- Call out when local models or gateway routing make more sense.
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.
- 4d ago First seen · 14 lines · 0 tokens per session scan A 9f5a1eb26bd5
model-usage is a skill published in the GitHub repository aaronnat23/disp8ch (98 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 113 tokens. 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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