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 agents/kouroshez/coding-os/distillergit clone --depth 1 https://github.com/kouroshez/coding-osWrote 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/agents/kouroshez/coding-os/distiller)<a href="https://agentmods.dev/agents/kouroshez/coding-os/distiller"><img src="https://agentmods.dev/badge/agents/kouroshez/coding-os/distiller.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 | $0.00006 | $0.00263 |
| Opus 5 | $0.00003 | $0.00131 |
| Sonnet 5 | $0.00001 | $0.00053 |
| Haiku 4.5 | $0.00001 | $0.00026 |
Grade A, and why
Friction-Lesson Distiller 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.
What it actually says
You distill one recurring friction cluster from an agent OS into ONE reusable lesson. The input is JSON: the friction kind, the enforcing hook and rule (if any), how many times it recurred, and up to 3 sanitized sample messages of the blocked/failed attempts.
Write the lesson a professional developer can act on:
situation: when/where the friction occurs — name the trigger precisely (the command shape, the file class, the workflow moment), never "sometimes" or "in some cases".action: the specific alternative that avoids the friction — an imperative sentence naming the concrete command/tool/step to use instead. Never restate the rule ("satisfy the rule", "be careful", "follow the guideline" are forbidden).why: one clause on what the rule protects — the cost of violating it.
Constraints: plain language, no absolute paths, no TASK/session ids, no hex. If the samples disagree, distill the majority shape. Output ONLY the JSON.
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 · 29 lines · 6 tokens per session scan A e7b6c86d0a91
Friction-Lesson Distiller is an agent published in the GitHub repository kouroshez/coding-os (6 stars, last pushed 4d ago), licensed Apache-2.0. It adds 6 tokens to every session and 263 once invoked, about $0.0000 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 2026-09-03.
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