benchmarking-expert

benchmarking-expert is an agent for coding agents from jkitchin/discopt. It costs 74 tokens per session (2,052 once invoked), scanned A, original, EPL-2.0.

A specialist assistant for the discopt benchmark harness, a program used to measure and compare optimization software. It explains the testing process, performance charts, and how to add new problem types.

In plain words
What is it for?
It is for planning performance studies, interpreting Dolan–Moré performance profiles, understanding phase gates, and extending the benchmark suite.
Why use it?
It helps turn benchmark results into understandable comparisons and keeps new tests aligned with the project’s evaluation process.

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/jkitchin/discopt/benchmarking-expert
Clone the repo
git clone --depth 1 https://github.com/jkitchin/discopt

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 benchmarking-expert

README.md
[![agentmods](https://agentmods.dev/badge/agents/jkitchin/discopt/benchmarking-expert.svg)](https://agentmods.dev/agents/jkitchin/discopt/benchmarking-expert)
Your own site
<a href="https://agentmods.dev/agents/jkitchin/discopt/benchmarking-expert"><img src="https://agentmods.dev/badge/agents/jkitchin/discopt/benchmarking-expert.svg" alt="Measured on agentmods" height="20"></a>
Per session 74 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,052 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 $0.00074 $0.02052
Opus 5 $0.00037 $0.01026
Sonnet 5 $0.00015 $0.00410
Haiku 4.5 $0.00007 $0.00205

Measured 3d ago against content hash b05953fc8486, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

benchmarking-expert 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 3d 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/agents/benchmarking-expert.md · 119 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. 3d ago First seen · 119 lines · 74 tokens per session scan A b05953fc8486

Subscribe to this mod's changes

benchmarking-expert is an agent published in the GitHub repository jkitchin/discopt (24 stars, last pushed 4d ago), licensed EPL-2.0. It adds 74 tokens to every session and 2,052 once invoked, about $0.0004 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.