agent-auto-sci-skills: Instructions file for GitHub Copilot

skills/urban-exposure-review-radar-workflow/subskills/academic-research-suite/ars/.github/copilot-instructions.md

agent-auto-sci-skills copilot-instructions.md is an instructions file for GitHub Copilot from Lzy599775/agent-auto-sci-skills. It costs 671 tokens per session, scanned A, original, MIT.

Instructions for using AI as an assistant in academic research and writing. It covers research, literature reviews, paper drafting and peer review, with people responsible for important decisions.

In plain words
What is it for?
Use its commands and workflows for literature reviews, paper outlines, full writing pipelines, reviewer feedback and citation checking.
Why use it?
It helps organize multi-step academic work and check claims, references and other common problems in AI-assisted research.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file.

This is Lzy599775/agent-auto-sci-skills's own configuration. It tells GitHub Copilot how to work on agent-auto-sci-skills 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 agent-auto-sci-skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Lzy599775/agent-auto-sci-skills. 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/Lzy599775/agent-auto-sci-skills/main/skills/urban-exposure-review-radar-workflow/subskills/academic-research-suite/ars/.github/copilot-instructions.md
Clone the repo
git clone --depth 1 https://github.com/Lzy599775/agent-auto-sci-skills

Made for: GitHub Copilot.

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 agent-auto-sci-skills copilot-instructions.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/lzy599775/agent-auto-sci-skills/copilot-instructions.svg)](https://agentmods.dev/instructions/lzy599775/agent-auto-sci-skills/copilot-instructions)
Your own site
<a href="https://agentmods.dev/instructions/lzy599775/agent-auto-sci-skills/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/lzy599775/agent-auto-sci-skills/copilot-instructions.svg" alt="Measured on agentmods" height="20"></a>
Per session 671 This file is loaded in full into every session.
When invoked 671 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 $0.00671 $0.00671
Opus 5 $0.00336 $0.00336
Sonnet 5 $0.00134 $0.00134
Haiku 4.5 $0.00067 $0.00067

Measured 7d ago against content hash 71178dbbcb46, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

agent-auto-sci-skills 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 7d 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.

skills/urban-exposure-review-radar-workflow/subskills/academic-research-suite/ars/.github/copilot-instructions.md · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Academic Research Skills for GitHub Copilot

AI-augmented research pipeline for academic writing, literature review, and peer review.

Core principle: AI is your copilot, not the pilot. Humans focus on substantive decisions; AI handles grunt work (references, formatting, verification).

Quick Start

Try /ars-plan — describe your paper, get Socratic structure guidance.

Key commands: /ars-lit-review, /ars-outline, /ars-full, /ars-reviewer, /ars-citation-check

Setup & Installation

SETUP.md for plugin, local symlink, API keys, and optional tools

Architecture & Components

  • Deep Research — 13-agent team, PRISMA support, intent detection
  • Paper Writing — 12-agent pipeline, style calibration, citation verification
  • Peer Review — 7-agent multi-perspective review, quality rubrics
  • Pipeline — 10-stage orchestration, claim verification, material passports

ARCHITECTURE.md for full flow diagrams and dependency graph

Integrity & Safety

Addresses AI research failure modes (Kong et al. 2026, arXiv:2605.18661):

  • 7-mode blocking checklist for common AI failures
  • Claim-level audits with locator anchors
  • Trust-chain frontmatter for provenance
  • FNR/FPR calibration on custom measures

⚠️ Permission modes: for unattended pipeline runs, Auto mode is the recommended setting (a server-side classifier still gates dangerous escalations). --dangerously-skip-permissions removes all safety checks and is only appropriate for isolated, no-internet sandboxes. See PERFORMANCE.md for full context before changing modes.

Contributing

CONTRIBUTING.md for PR workflow, acceptance criteria, development guidelines

Docs

Topic Link
Setup & Installation SETUP.md
Architecture ARCHITECTURE.md
Performance & Costs PERFORMANCE.md
Design Philosophy POSITIONING.md
Contributing CONTRIBUTING.md
Citation CITATION.cff

Read the full file on GitHub · 65 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. 7d ago First seen · 65 lines · 671 tokens per session scan A 71178dbbcb46

Subscribe to this mod's changes

agent-auto-sci-skills copilot-instructions.md is an instructions file published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed yesterday), licensed MIT. It adds 671 tokens to every session, about $0.0034 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.

Related

Other instructions, from other repositories

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens