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 hashgraph-online/awesome-codex-plugins --skill cassette-modelgit clone --depth 1 https://github.com/hashgraph-online/awesome-codex-pluginsWrote 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/hashgraph-online/awesome-codex-plugins/cassette-model)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/cassette-model"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/cassette-model.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 5.1 | $0.00050 | $0.00351 |
| Opus 5 | $0.00025 | $0.00176 |
| Sonnet 5 | $0.00010 | $0.00070 |
| Haiku 4.5 | $0.00005 | $0.00035 |
Grade A, and why
cassette-model 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 yesterday.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- cassette-model — 100% identical, 0 lines differ
What it actually says
Cassette model picker
This is an explicit settings action. Never invoke it automatically during media ingestion or before
an edit. A fresh Cassette session already uses GPT-5.6 Luna with xhigh thinking.
- Reuse the active Cassette
session_idfrom the current conversation. If no Cassette media session exists yet, tell the user to add media first; do not invent an id or create an edit. - Call
cassette_configwith onlysession_idto read the current selection and static options. - If the invocation already names a valid model and/or thinking level, call
cassette_configwith those values and confirm the saved choice in one line. - Otherwise show the model and thinking choices as two compact numbered lists and wait for the
user's selections. Then call
cassette_configwith the selected model label and thinking value. - Explain that the setting is scoped to this Cassette session and applies from the next edit turn.
Selectable models are GPT-5.6 Luna and GPT-5.4 Mini. Thinking values are off, minimal, low,
medium, high, and xhigh (display xhigh as “Extra High”).
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.
- yesterday First seen · 27 lines · 50 tokens per session scan A b5a0636a8aa2
cassette-model is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (935 stars, last pushed today), licensed Apache-2.0. It adds 50 tokens to every session and 351 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 2026-09-05.
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