explain-model

A command that reads a discopt optimization model and writes its formal mathematical description in LaTeX or Markdown. The write-up covers the model's sets, inputs, decisions, goal, and rules, with plain-English explanations.

In plain words
What is it for?
Use it to create technical documentation for a discopt model or produce a math-focused explanation for developers and model reviewers.
Why use it?
It removes the need to manually translate modeling code into mathematical notation and explanatory text. This makes an optimization model easier to document and review.

Command

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 commands/jkitchin/discopt/explain-model
Clone the repo
git clone --depth 1 https://github.com/jkitchin/discopt
Per session 46 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,439 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00046 $0.01439
Opus 5 $0.00023 $0.00720
Sonnet 5 $0.00009 $0.00288
Haiku 4.5 $0.00005 $0.00144

Measured 2d ago against content hash 3056946f22eb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

explain-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 2d 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.

python/discopt/skills/commands/explain-model.md · 122 lines

The source is not reproduced here

Licensed EPL-2.0

The repository is licensed EPL-2.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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. 2d ago First seen · 122 lines · 46 tokens per session scan A 3056946f22eb

Subscribe to this mod's changes

explain-model is a command published in the GitHub repository jkitchin/discopt (24 stars, last pushed 3d ago), licensed EPL-2.0. It adds 46 tokens to every session and 1,439 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.