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.
git clone --depth 1 https://github.com/marcos-dv/ampl-agentsnpx agentmods add skills/marcos-dv/ampl-agents/ampl-energyWrote 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/marcos-dv/ampl-agents/ampl-energy)<a href="https://agentmods.dev/skills/marcos-dv/ampl-agents/ampl-energy"><img src="https://agentmods.dev/badge/skills/marcos-dv/ampl-agents/ampl-energy/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/marcos-dv/ampl-agents/ampl-energy"><img src="https://agentmods.dev/badge/skills/marcos-dv/ampl-agents/ampl-energy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00089 | $0.03447 |
| Opus 5.5 | $0.00036 | $0.01379 |
| Sonnet 5.5 | $0.00018 | $0.00689 |
| Haiku 4.5 | $0.00009 | $0.00345 |
Grade A, and why
ampl-energy 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 2mo 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): How it starts
The opening of the file, as written. The whole thing — 393 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AMPL Energy Skill
Always-on constraints (verified solve, model structure, verified references) live in
rules/and apply whenever this skill is active.
Mission
You model energy and power systems in AMPL with clear, readable constraints — often using logical operators and MP reformulation rather than opaque big-M spreadsheets. You cover linear, MIP, conic, and nonlinear (MINLP/NLP) formulations as appropriate. You leverage AMPL's efficient instantiation of multi-period, multi-unit, and network-indexed models.
You recommend solvers and tuning for large MIPs (unit commitment) and nonlinear OPF. You align with verified Colab electric-power notebooks when citing examples.
Code examples convention
Every snippet lists Preferred: amplpy first, then Pure AMPL. Put model structure in model.mod + ampl.read().
Environment
Assume amplpy is installed and licensed — delegate setup to ampl-installer if not.
from amplpy import AMPL
ampl = AMPL()
Energy MIPs often need gurobi, xpress cplex or copt; MINLP UC may need knitro, gurobi or xpress; conic models may need mosek — request matching modules via ampl-installer.
Solver classification (commercial vs open-source)
Sources: https://dev.ampl.com/solvers/index.html , https://dev.ampl.com/ampl/python/modules.html
Open-source: HiGHS (LP/MIP prototype), SCIP (MIP), and for nonlinear problems Ipopt/Bonmin/Couenne via coin.
Commercial (typical for production energy):
| Solver | Energy use |
|---|---|
| gurobi, xpress, cplex | Unit commitment MIP, large transmission MIP |
| mosek, copt | Conic hydrothermal, SOCP relaxations |
| knitro | MINLP UC with nonlinear heat rates (Colab UC MINLP notebook) |
NEOS: gokestrel on Colab for trials without local commercial license.
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.
- 2mo ago First seen · 393 lines · 89 tokens per session scan A b70ff6db75e8
ampl-energy is a skill published in the GitHub repository marcos-dv/ampl-agents (10 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 3,447 once invoked, about $0.0004 per session on Opus 5.5. 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.
ampl-energy compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ampl-energymarcos-dv/ampl-agents | Skill | 10 | 2mo ago | MIT | A | 89 | Claude Code, Codex |
| manimce-best-practicescalesthio/OpenMontage | Skill | 78k | 5d ago | AGPL-3.0 | A | 149 | Claude Code, Codex |
| torchtalk-analyzeropendatahub-io/ai-helpers | Skill | 39 | 4d ago | Apache-2.0 | A | 58 | Claude Code |
| torchtalk-traceopendatahub-io/ai-helpers | Skill | 39 | 4d ago | Apache-2.0 | A | 24 | Claude Code |
| torchtalk-setupopendatahub-io/ai-helpers | Skill | 39 | 4d ago | Apache-2.0 | B | 19 | Claude Code |
| postgresql-table-designwshobson/agents | Skill | 42k | 4d ago | MIT | A | 37 | Claude Code |
| parallel-feature-developmentwshobson/agents | Skill | 42k | 4d ago | MIT | A | 105 | Claude Code |