Friction-Lesson Distiller

Friction-Lesson Distiller is an agent for coding agents from kouroshez/coding-os. It costs 6 tokens per session (263 once invoked), scanned A, original, Apache-2.0.

A lesson-writing tool that turns repeated problems in an AI agent workflow into one practical instruction for developers.

In plain words
What is it for?
Use it to record when a problem happens, the alternative action that avoids it, and the cost of ignoring the relevant rule.
Why use it?
It helps teams learn from recurring blocked or failed attempts instead of solving the same workflow problem repeatedly.

Agent

Install

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.

agentmods
npx agentmods add agents/kouroshez/coding-os/distiller
Clone the repo
git clone --depth 1 https://github.com/kouroshez/coding-os

Wrote 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.

agentmods badge for Friction-Lesson Distiller

README.md
[![agentmods](https://agentmods.dev/badge/agents/kouroshez/coding-os/distiller.svg)](https://agentmods.dev/agents/kouroshez/coding-os/distiller)
Your own site
<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>
Per session 6 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 263 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured yesterday against content hash e7b6c86d0a91, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

src/core/thinking_os/agents/distiller.md · 29 lines

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.

Changes

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.

  1. yesterday First seen · 29 lines · 6 tokens per session scan A e7b6c86d0a91

Subscribe to this mod's changes

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.