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geval: Instructions file for GitHub Copilot

.github/copilot-instructions.md

geval copilot-instructions.md is an instructions file for GitHub Copilot from geval-labs/geval. It costs 846 tokens per session, scanned A, original, MIT.

Repository instructions for Geval, a Rust command-line tool that applies YAML rules to JSON signals and returns a policy outcome.

In plain words
What is it for?
Use them when editing Geval, running its checks, or working with its command-line interface, policies, signals, and exit codes.
Why use it?
They give a coding agent the project layout, build and test commands, and the tool's rule-reconciliation behavior, reducing guesswork when changing the code.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file.

This is geval-labs/geval's own configuration. It tells GitHub Copilot how to work on geval itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything geval configures →

not rated 44repo 7mo ago A scan 846 tokens original MIT
View source ↗ geval-labs/geval geval.io
Reuse

Borrowing it

Nothing to install: this file belongs to geval-labs/geval. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/geval-labs/geval/main/.github/copilot-instructions.md
Clone the repo
git clone --depth 1 https://github.com/geval-labs/geval

Made for: GitHub Copilot.

Wrote this? Show the measurements

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Per session 846 This file is loaded in full into every session.
When invoked 846 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00846 $0.00846
Opus 5.5 $0.00338 $0.00338
Sonnet 5.5 $0.00169 $0.00169
Haiku 4.5 $0.00085 $0.00085

Measured 2mo ago against content hash 801bcb8065a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

geval copilot-instructions.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 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.

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.

.github/copilot-instructions.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Geval - AI Coding Instructions

Project Overview

Geval is a decision orchestration and reconciliation tool for AI systems. It consumes signals (JSON) and policy (YAML), evaluates all rules (unique priorities; 1 = highest), surfaces every match, applies the best-priority winner per policy, and merges policies/contracts with worst_case (BLOCK > REQUIRE_APPROVAL > PASS). It does not run evals, call APIs, or compute metrics—it only reconciles your rules against your signals.

Core Philosophy: Geval has no “brain.” You provide signals and rules; Geval applies the rules and returns one outcome. Same inputs + same policy = same outcome.

Repository Structure

  • geval/ – Rust crate (the only product)
    • src/ – CLI and engine (commands, evaluator, signals loader, policy parser)
    • docs/ – User docs (installation, GitHub Actions, signals and rules, auditing)
    • examples/ – Sample signals.json and policy.yaml for local/CI use
    • scripts/ – e.g. generate_signals.py for CI demo
  • .github/workflows/ – CI (build + test Rust) and release (build binary on tag push)
  • Root: README, CONTRIBUTING, LICENSE, CODE_OF_CONDUCT

There are no npm packages, no TypeScript, no Turborepo. The artifact is a single Rust binary distributed via GitHub Releases.

Build and Test

  • Build: cargo build --release --manifest-path geval/Cargo.toml
  • Test: cargo test --manifest-path geval/Cargo.toml
  • Binary: geval/target/release/geval (or geval.exe on Windows)

Run from repo root: ./geval/target/release/geval demo or geval check --signals ... --policy ... once the binary is on PATH.

CLI and Exit Codes

  • Commands: geval demo, geval init, geval check, geval explain, geval approve / geval reject (see geval --help).
  • Exit codes (for CI):
    • 0 – PASS
    • 1 – REQUIRE_APPROVAL
    • 2 – BLOCK
    • Non-zero on error (e.g. missing file, invalid JSON/YAML).

Read the full file on GitHub · 57 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. 2mo ago First seen · 57 lines · 846 tokens per session scan A 801bcb8065a5

Subscribe to this mod's changes

geval copilot-instructions.md is an instructions file published in the GitHub repository geval-labs/geval (44 stars, last pushed 7mo ago), licensed MIT. It adds 846 tokens to every session, about $0.0034 per session on Opus 5.5. 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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