ai-engineering-fluency: Instructions file for GitHub Copilot

.github/instructions/sharing-server.instructions.md

ai-engineering-fluency sharing-server.instructions.md is an instructions file for GitHub Copilot from rajbos/ai-engineering-fluency. It costs 171 tokens per session, scanned A, original, MIT.

Coding and testing guidance for a server that separates personal data from identity-free team summaries and administrator details. It also defines how to test those privacy rules with local database fixtures and stubbed GitHub access.

In plain words
What is it for?
Use it when changing server code, tests, documentation, or route overrides that handle user data and GitHub-backed results.
Why use it?
It reduces the risk of exposing private information or creating inconsistent privacy rules across routes, tests, and documentation.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file. Also seen: mentions AGENTS.md.

This is rajbos/ai-engineering-fluency's own configuration. It tells GitHub Copilot how to work on ai-engineering-fluency 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 ai-engineering-fluency configures →

Reuse

Borrowing it

Nothing to install: this file belongs to rajbos/ai-engineering-fluency. 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/rajbos/ai-engineering-fluency/main/.github/instructions/sharing-server.instructions.md
Clone the repo
git clone --depth 1 https://github.com/rajbos/ai-engineering-fluency

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 ai-engineering-fluency sharing-server.instructions.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/rajbos/ai-engineering-fluency/sharing-server/github.svg)](https://agentmods.dev/instructions/rajbos/ai-engineering-fluency/sharing-server)
Your own site
<a href="https://agentmods.dev/instructions/rajbos/ai-engineering-fluency/sharing-server"><img src="https://agentmods.dev/badge/instructions/rajbos/ai-engineering-fluency/sharing-server/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ai-engineering-fluency sharing-server.instructions.md

Your own site · 80×15
<a href="https://agentmods.dev/instructions/rajbos/ai-engineering-fluency/sharing-server"><img src="https://agentmods.dev/badge/instructions/rajbos/ai-engineering-fluency/sharing-server.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 171 This file is loaded in full into every session.
When invoked 171 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 $0.00171 $0.00171
Opus 5.5 $0.00068 $0.00068
Sonnet 5.5 $0.00034 $0.00034
Haiku 4.5 $0.00017 $0.00017

Measured yesterday against content hash 57f9bb6bd21d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-engineering-fluency sharing-server.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 yesterday.

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/sharing-server.instructions.md · 18 lines

What it actually says

Sharing server — coding and testing

Read and follow sharing-server/AGENTS.md, the authoritative data separation contract, before changing server code, tests, documentation or downstream route overrides. It defines owner-only personal data, identity-free team projections, server-authorized admin detail, exact comparison semantics and HTTP/HTML privacy regression coverage.

Use the server check-types, build, test and headless check:interaction scripts as described there, including the existing Playwright/Chromium prerequisite. Use isolated SQLite fixtures and stubbed GitHub access, never production data or live GitHub. Keep implementation and testing descriptions linked to the contract rather than creating alternative privacy rules.

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. yesterday First seen · 18 lines · 171 tokens per session scan A 57f9bb6bd21d

Subscribe to this mod's changes

ai-engineering-fluency sharing-server.instructions.md is an instructions file published in the GitHub repository rajbos/ai-engineering-fluency (119 stars, last pushed yesterday), licensed MIT. It adds 171 tokens to every session, about $0.0007 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 2026-10-26.

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