copilot-benchmark

A benchmark suite for testing how well the Copilot command-line agent answers questions about a code repository, with and without Lore tools.

In plain words
What is it for?
It is for running repeated benchmark tasks against repositories such as Zod, FastAPI, esbuild, Postgres, and Gson, then comparing the results.
Why use it?
It measures whether the added tools improve answer correctness, coverage, and efficiency rather than relying on impressions.

Skill for Claude CodeCodex

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 skills/jafreck/lore/copilot-benchmark
Any agent
npx skills add jafreck/Lore --skill copilot-benchmark
Clone the repo
git clone --depth 1 https://github.com/jafreck/Lore

Made for: Claude Code, Codex.

Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,506 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00043 $0.01506
Opus 5 $0.00022 $0.00753
Sonnet 5 $0.00009 $0.00301
Haiku 4.5 $0.00004 $0.00151

Measured 2d ago against content hash 537c3fb4c705, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

copilot-benchmark 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.

.github/skills/copilot-benchmark/SKILL.md · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Copilot Agent Benchmark

Purpose

Run Lore's Copilot agent benchmark harness, which evaluates how the Copilot CLI answers codebase questions with and without Lore MCP tools, comparing the two arms on correctness, coverage, and efficiency.

Prerequisites

  • copilot CLI installed and authenticated (copilot --version must work).
  • Node.js 22 (use nvm use 22).
  • Lore built (npm run build) — the test beforeAll also runs this.
  • Real API calls are made — this costs tokens.

Quick start

source ~/.nvm/nvm.sh && nvm use 22
npm run build
BENCHMARK_COPILOT=1 npx vitest run tests/benchmark/copilot-agent.test.ts

Environment variables

Variable Default Description
BENCHMARK_COPILOT (unset) Required. Set to 1 to enable the suite (skipped otherwise).
BENCHMARK_REPO lore-self Target repo. Options: lore-self, zod, fastapi, esbuild, postgres, gson.
BENCHMARK_MODEL claude-opus-4.6 LLM model passed to copilot CLI --model.
BENCHMARK_INDEX_MODE scip Lore indexing mode: tree-sitter, scip, or full.
BENCHMARK_ITERATIONS 1 Runs per task. Use ≥3 for statistical significance.
BENCHMARK_EMBEDDING_MODEL (empty) Embedding model, e.g. nomic-ai/nomic-embed-text-v1.5.
BENCHMARK_LSP (unset) Set to 1 to enable LSP enrichment during indexing.

Instructions

When the user asks to run, execute, or launch a Copilot benchmark:

  1. Pre-flight checks

    • Ensure Node.js 22 is active: source ~/.nvm/nvm.sh && nvm use 22.
    • Build Lore: npm run build.
    • Verify copilot --version works.
  2. Determine configuration from user request

    • Pick a repo from the available list. Default is lore-self.
    • Pick an index mode. Default is scip.
    • Pick iteration count. Default is 1 for quick runs, 3+ for statistical significance.
    • Pick model. Default is claude-opus-4.6.
  3. Run the benchmark

    • Launch as a background process since it runs for 10–20 minutes:
    BENCHMARK_COPILOT=1 \
      BENCHMARK_REPO=lore-self \
      BENCHMARK_INDEX_MODE=scip \
      BENCHMARK_ITERATIONS=1 \
      npx vitest run tests/benchmark/copilot-agent.test.ts
    

Read the full file on GitHub · 126 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 · 126 lines · 43 tokens per session scan A 537c3fb4c705

Subscribe to this mod's changes

copilot-benchmark is a skill published in the GitHub repository jafreck/Lore (7 stars, last pushed 16d ago), licensed MIT. It adds 43 tokens to every session and 1,506 once invoked, about $0.0002 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 2026-08-31.

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