Awesome-Agentic-Engineering link-and-source-quality.instructions.md

Awesome-Agentic-Engineering link-and-source-quality.instructions.md is an instructions file for GitHub Copilot from natnew/Awesome-Agentic-Engineering. It costs 242 tokens per session, scanned A, original, MIT.

Guidance for judging the quality and reliability of links and sources in a catalogue or research list.

In plain words
What is it for?
Use it to check whether links resolve, point to canonical destinations, come from maintained projects, and support claims with suitable evidence labels.
Why use it?
It helps separate official, durable technical evidence from marketing pages, unverifiable claims, redirects, and popularity measures such as repository stars.

Instructions file for GitHub Copilot

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/natnew/awesome-agentic-engineering/link-and-source-quality
Clone the repo
git clone --depth 1 https://github.com/natnew/Awesome-Agentic-Engineering

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 Awesome-Agentic-Engineering link-and-source-quality.instructions.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/natnew/awesome-agentic-engineering/link-and-source-quality.svg)](https://agentmods.dev/instructions/natnew/awesome-agentic-engineering/link-and-source-quality)
Your own site
<a href="https://agentmods.dev/instructions/natnew/awesome-agentic-engineering/link-and-source-quality"><img src="https://agentmods.dev/badge/instructions/natnew/awesome-agentic-engineering/link-and-source-quality.svg" alt="Measured on agentmods" height="20"></a>
Per session 242 This file is loaded in full into every session.
When invoked 242 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 $0.00242 $0.00242
Opus 5 $0.00121 $0.00121
Sonnet 5 $0.00048 $0.00048
Haiku 4.5 $0.00024 $0.00024

Measured 4d ago against content hash fbcf03017ef8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Awesome-Agentic-Engineering link-and-source-quality.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 4d 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/instructions/link-and-source-quality.instructions.md · 27 lines

What it actually says

How to assess the links and sources behind an entry.

Prefer durable, canonical sources

  • Favour official documentation, papers, canonical repositories, technical write-ups, datasets, and durable project pages.
  • Link to the canonical destination, not a redirect, an aggregator, or a tracking URL.
  • Separate benchmark performance from production maturity: a benchmark proves workload fit, not reliability.

Treat these with caution

  • Thin landing or marketing pages, affiliate-style pages, and press releases.
  • Unverifiable claims, launch-day numbers without methodology, and cherry-picked metrics.
  • Excessive self-promotion, and generic or AI-generated content with no engineering substance.
  • GitHub stars used as evidence — popularity is not reliability.

Before accepting a resource

  • Confirm it appears maintained, relevant to the list's scope, and technically useful.
  • Check that each substantive claim carries an appropriate evidence tag: [official], [benchmark], [field report], or [author assessment].
  • Verify every link resolves. When a section changes quickly, confirm its Last reviewed: marker is current.
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. 4d ago First seen · 27 lines · 242 tokens per session scan A fbcf03017ef8

Subscribe to this mod's changes

Awesome-Agentic-Engineering link-and-source-quality.instructions.md is an instructions file published in the GitHub repository natnew/Awesome-Agentic-Engineering (4 stars, last pushed 10d ago), licensed MIT. It adds 242 tokens to every session, about $0.0012 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

Awesome-Prompt-Engineering AGENTS.md

Instructions for natnew/Awesome-Prompt-Engineering, covering agents.md, repository north star, agent role, trust boundary and read order.

natnew/Awesome-Prompt-Engineering · 2,054 tokens

Awesome-Prompt-Engineering CLAUDE.md

Instructions for natnew/Awesome-Prompt-Engineering, covering claude.md, north star, claude's role, claude behaviour rule and always-loaded context.

natnew/Awesome-Prompt-Engineering · 1,800 tokens

Awesome-Prompt-Engineering copilot-instructions.md

Instructions for natnew/Awesome-Prompt-Engineering, covering github copilot instructions, about this repository, how to treat the repository, contribution standard and reviewing suggested additions.

natnew/Awesome-Prompt-Engineering · 1,416 tokens

Awesome-Prompt-Engineering contribution-review.instructions.md

Instructions for natnew/Awesome-Prompt-Engineering, covering reviewing pull requests and issues, tone, how to respond, explaining quality concerns and maintainer judgement.

natnew/Awesome-Prompt-Engineering · 403 tokens

Awesome-Prompt-Engineering readme-curation.instructions.md

Instructions for natnew/Awesome-Prompt-Engineering, covering curating the main list (readme.md), structure and ordering, descriptions, links and before adding.

natnew/Awesome-Prompt-Engineering · 432 tokens

Awesome-Prompt-Engineering repository-maintenance.instructions.md

Instructions for natnew/Awesome-Prompt-Engineering, covering maintenance edits across markdown files, keep changes minimal, preserve voice and structure, no large or structural changes without direction and readability.

natnew/Awesome-Prompt-Engineering · 368 tokens