copilot-instructions: Instructions file for GitHub Copilot

.github/instructions/data-privacy-compliance.instructions.md

copilot-instructions data-privacy-compliance.instructions.md is an instructions file for GitHub Copilot from ThiagoGuislotti/copilot-instructions. It costs 566 tokens per session, scanned A, original, MIT.

A baseline for privacy and compliance when an application handles personal data. It covers data inventories, classification, minimization, consent, legal basis, pseudonymization, access control, and separation of data.

In plain words
What is it for?
Use it when designing APIs, frontends, backends, or databases that process personal data, especially when defining retention, consent records, permissions, and downstream data handling.
Why use it?
It helps teams identify privacy risks early and avoid collecting, retaining, or sharing personal data without a clear purpose and control.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file.

This is ThiagoGuislotti/copilot-instructions's own configuration. It tells GitHub Copilot how to work on copilot-instructions 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 copilot-instructions configures →

Reuse

Borrowing it

Nothing to install: this file belongs to ThiagoGuislotti/copilot-instructions. 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/ThiagoGuislotti/copilot-instructions/main/.github/instructions/data-privacy-compliance.instructions.md
Clone the repo
git clone --depth 1 https://github.com/ThiagoGuislotti/copilot-instructions

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.

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README.md
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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.

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Your own site · 80×15
<a href="https://agentmods.dev/instructions/thiagoguislotti/copilot-instructions/data-privacy-compliance"><img src="https://agentmods.dev/badge/instructions/thiagoguislotti/copilot-instructions/data-privacy-compliance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 566 This file is loaded in full into every session.
When invoked 566 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 $0.00566 $0.00566
Opus 5.5 $0.00226 $0.00226
Sonnet 5.5 $0.00113 $0.00113
Haiku 4.5 $0.00057 $0.00057

Measured 1mo ago against content hash 39c72b139024, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

copilot-instructions data-privacy-compliance.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 1mo 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/data-privacy-compliance.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.

Data Privacy and Compliance Baseline

  • Use this instruction for privacy-by-design decisions across API, frontend, backend, and database layers.
  • Treat personal data handling as an explicit architecture concern, not only a legal review step.

Scope and Governance

  • Maintain a current data inventory with owner, purpose, sensitivity class, and retention policy.
  • Classify data at minimum as public, internal, confidential, and restricted.
  • Define accountability for each processing activity and audit ownership.

Privacy by Design

  • Apply data minimization; collect and retain only what is necessary for the declared purpose.
  • Enforce purpose limitation; prevent uncontrolled reuse of collected data.
  • Prefer pseudonymization or tokenization for identifiers in non-core processing flows.
  • Separate operational identifiers from personal identifiers whenever feasible.
  • Record legal basis and consent state for processing operations that require it.
  • Keep auditable records of consent capture, updates, and withdrawal events.
  • Propagate consent constraints to downstream systems and derived datasets.

Access Control and Segregation

  • Enforce least privilege access to personal data by role and business purpose.
  • Segment privileged access paths and require elevated controls for sensitive datasets.
  • Protect multi-tenant boundaries with strict tenant-scoped access checks.

Data Protection Controls

  • Encrypt personal and sensitive data in transit and at rest.
  • Use managed key lifecycle controls including rotation and access auditing.
  • Mask or redact personal data in logs, telemetry, and non-production datasets.
  • Prohibit secrets and personal data leakage in error messages and debug outputs.

Retention, Deletion, and Archival

  • Define retention schedules per data class and enforce automated expiration where feasible.
  • Implement deletion workflows that include primary stores, replicas, caches, and derived datasets.
  • Validate backup and archival deletion semantics against retention and legal constraints.
  • Maintain verifiable evidence of deletion and retention policy execution.

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. 1mo ago First seen · 57 lines · 566 tokens per session scan A 39c72b139024

Subscribe to this mod's changes

copilot-instructions data-privacy-compliance.instructions.md is an instructions file published in the GitHub repository ThiagoGuislotti/copilot-instructions (2 stars, last pushed 3mo ago), licensed MIT. It adds 566 tokens to every session, about $0.0023 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 2026-08-31.

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