RigorLoop AGENTS.md

Repository instructions for RigorLoop, a Python command-line tool that runs repeated agent tasks against example answers and checks. It helps produce scripts, agent skills, or guidance files and follows a functional-core, imperative-shell design.

In plain words
What is it for?
Understanding the package, following its development workflow, implementing loop-engineering features, and using its init, check, run, and report commands.
Why use it?
It explains the project's architecture and strict coding rules so changes fit the existing design and can be evaluated reliably.

Instructions file for CodexOpenCode

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 instructions/ronikobrosly/rigorloop/agents-md
Clone the repo
git clone --depth 1 https://github.com/ronikobrosly/RigorLoop

Made for: Codex, OpenCode.

Per session 1,515 This file is loaded in full into every session.
When invoked 1,515 The same file — it is already loaded in full.
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 $0.01515 $0.01515
Opus 5 $0.00758 $0.00758
Sonnet 5 $0.00303 $0.00303
Haiku 4.5 $0.00152 $0.00152

Measured 2d ago against content hash 275598bc3a64, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

RigorLoop AGENTS.md 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.

AGENTS.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Orientation for coding agents working in this repository. Read this first, then read CODING_STYLE.md before writing or modifying any code — its rules are hard constraints, not preferences.

What this package is

RigorLoop is a statistically-sound agentic loop-engineering framework. You give it a task description, a pile of gold-standard input/output examples, and a set of checks; it runs agentic loops (a strategy agent directing concurrent executor agents) that iteratively build a solution and evaluate it on a strict dev / validation / test split, so the final score is trustworthy. The produced artifact is portable: an executable Python script, an agent skill (SKILL.md), or a guidance file (AGENTS.md/CLAUDE.md).

  • Pure Python, stdlib-only by design (no runtime dependencies), Python ≥ 3.12.
  • Ships a single CLI: rigorloop (init / check / run / report).
  • Invokes agents headless and tool-less via the claude CLI (claude -p).
  • User-facing docs: README.md. Contributing: CONTRIBUTING.md.

Architecture: functional core / imperative shell

This is the single most important thing to understand, and it is enforced by CODING_STYLE.md:

  • src/rigorloop/core/ — the functional core. 100% pure: no I/O, no mutation, no time, no randomness, no network, no environment access. It decides; it returns values and plans of effects. Testable with plain inputs and zero mocks. Core coverage is held to a higher bar (≥95%).
  • src/rigorloop/shell/ — the thin imperative shell. Performs all effects (filesystem, subprocess, the claude CLI) and hands plain data to the core. Keep it small.

The dev/val/test split is encoded in the type system (DevExample, ValExample, TestExample) so leaking holdout data into an agent-context prompt is a type error, not a runtime bug. Don't defeat this.

Working in this repo

  • Dev commands live in the justfile, each mirroring a CI job: just lint, just typecheck, just test, just check (all three), just fmt.
  • Tooling: uv for env/build, ruff (lint + format), mypy --strict, pytest. T20 (print) is banned in the core and allowed in the shell.
  • Every source module has a sibling test in tests/ (e.g. scoring_calcs.pytest_scoring_calcs.py); test_leakage.py guards the split-type invariant and test_e2e.py runs full loops against fake agents.

Read the full file on GitHub · 122 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. 2d ago First seen · 122 lines · 1,515 tokens per session scan A 275598bc3a64

Subscribe to this mod's changes

RigorLoop AGENTS.md is an instructions file published in the GitHub repository ronikobrosly/RigorLoop (77 stars, last pushed 1mo ago), licensed MIT. It adds 1,515 tokens to every session, about $0.0076 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.

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