ampl-tuner

ampl-tuner is a skill for Claude Code, Codex from marcos-dv/ampl-agents. It costs 99 tokens per session (8,175 once invoked), scanned A, original, MIT.

A specialist guide for choosing settings for AMPL optimization solvers. AMPL is a language for describing mathematical optimization problems, and solvers find their best solution.

In plain words
What is it for?
Use it to set time limits, acceptable solution gaps, thread counts, infeasibility analysis, and algorithm choices for LP, MIP, QP, NLP, MINLP, and conic problems.
Why use it?
It helps avoid guessing solver settings or using undocumented options. It first checks the official solver documentation and keeps recommendations focused on the type of optimization problem.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is Always-on constraints ([verified references](../../rules/ampl-verified-references.md)) live in [`rules/`](../../rules/) and apply whenever this skill is active..

Good fit Use it to set time limits, acceptable solution gaps, thread counts, infeasibility analysis, and algorithm choices for LP, MIP, QP, NLP, MINLP, and conic problems.

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Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/marcos-dv/ampl-agents
agentmods
npx agentmods add skills/marcos-dv/ampl-agents/ampl-tuner

Made for: Claude Code, Codex.

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 ampl-tuner

README.md
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Your own site
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agentmods 80×15 button for ampl-tuner

Your own site · 80×15
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Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,175 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00099 $0.08175
Opus 5 $0.00049 $0.04088
Sonnet 5 $0.00020 $0.01635
Haiku 4.5 $0.00010 $0.00817

Measured 10d ago against content hash 3f0d806e490f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ampl-tuner scanned grade A with 1 finding 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 10d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

IF you have internet access (WebFetch, browser, or curl):
skills/ampl-tuner/SKILL.md · 652 lines

How it starts

The opening of the file, as written. The whole thing — 652 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AMPL Tuner Skill

Always-on constraints (verified references) live in rules/ and apply whenever this skill is active.

Mission

You are the solver options specialist for AMPL and MP drivers. You know how options flow through mp_options, ampl.option, and <solver>_options, and you recommend minimal, justified option sets for the user's problem class (LP, MIP, QP, NLP, MINLP, conic).

You fetch https://dev.ampl.com/solvers/<solver>/options.html when online and quote option names verbatim from that page. You do not invent undocumented options. You do not reformulate models — delegate structural changes to ampl-modeler or domain skills.


Code examples convention

Every option snippet lists Preferred: amplpy first, then Pure AMPL.


How options are passed

MP-wide (mp_options)

Cross-solver driver options (verbosity, IIS, rays, termination criteria):

Preferred: amplpy:

ampl.solve(
    solver="gurobi",
    mp_options="outlev=1 lim:time=300 iisfind=0",
    gurobi_options="lim:time=300 mip:gap=0.01 mip:focus=1",
)

Pure AMPL:

option solver gurobi;
option mp_options 'outlev=1 lim:time=300';
option gurobi_options 'lim:time=300 mip:gap=0.01 mip:focus=1';
solve;

AMPL global

From https://dev.ampl.com/ampl/options.html (or ampl/reference/options.html).

Option Default Purpose
presolve on AMPL presolve; set 0 before IIS or to allow more substout eliminations
linelim 1 Substitute linear defined variables into objectives/constraints so underlying vars stay linear; 0 treats them as nonlinear
substout 0 1: convert eligible var = expr constraints into defined variables (scan order matters)

Preferred: amplpy:

ampl.option["linelim"] = 1      # keep LP linear when using defined vars (default)
ampl.option["substout"] = 0     # 1 to infer substitutions from defining constraints
ampl.option["presolve"] = 0       # disable AMPL presolve (often needed for IIS)

Read the full file on GitHub · 652 lines

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. 10d ago First seen · 652 lines · 99 tokens per session scan A 3f0d806e490f

Subscribe to this mod's changes

ampl-tuner is a skill published in the GitHub repository marcos-dv/ampl-agents (10 stars, last pushed 20d ago), licensed MIT. It adds 99 tokens to every session and 8,175 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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