agentic-playwright data-strategy.instructions.md

A data-handling guide for a TypeScript test framework that separates fixed test cases from generated test data. Static data is fixed in advance; factories create fresh values when tests run.

In plain words
What is it for?
Use it to decide where test values belong, create isolated data, validate generated values, and manage shared invalid-value examples.
Why use it?
It makes tests repeatable while avoiding collisions and hardcoded content that can make tests dependent on one another.

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/idavidov13/agentic-playwright/data-strategy
Clone the repo
git clone --depth 1 https://github.com/idavidov13/agentic-playwright

Made for: GitHub Copilot.

Per session 2,684 This file is loaded in full into every session.
When invoked 2,684 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 $0.02684 $0.02684
Opus 5 $0.01342 $0.01342
Sonnet 5 $0.00537 $0.00537
Haiku 4.5 $0.00268 $0.00268

Measured 2d ago against content hash 5637b1186f40, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agentic-playwright data-strategy.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 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/instructions/data-strategy.instructions.md · 232 lines

How it starts

The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Strategy

This framework uses a bifurcated data strategy: static data for deterministic curated cases and dynamic factories for test isolation.

Critical

  • Static data files are TypeScript only. Every file under test-data/static/** is a .ts file that exports as const literal values. NEVER use .json.
  • Static data files may only export literal values. No runtime imports (type-only imports are fine), no function definitions, no computed values, no Faker calls. Dynamic data belongs in factories, not in static files.
  • NEVER hardcode test content strings (names, emails, todo text, product names, descriptions, etc.) in a spec file. Generate with a Faker factory.
  • NEVER redefine universal type-mismatch arrays ([123, true, null, undefined], etc.) inline. Import them from test-data/static/util/invalid-values.ts.
  • ALWAYS validate factory output with Schema.parse(...) and return the Zod-inferred type.
  • NEVER generate app-defined strings with Faker (error messages, button labels, page headers). Those live in enums/ so they stay in sync with the application under test.
  • NEVER store fixed expected values that are used in a single assertion in a static data file. Keep them inline in the test.
  • ALWAYS follow the refactor-values skill before editing any existing static-data file or enum value — these edits cascade through assertions and data-driven loops.
  • NEVER introduce magic numbers (timeouts, retry counts, limits) inline. Prefer web-first assertions; when a numeric value is unavoidable, route it through playwright.config.ts or an enum in enums/.

File Locations

{area} is a placeholder. Before creating or referencing any path below, run ls test-data/static/ and ls test-data/factories/ to discover the real subdirectory names in this repo (e.g., front-office, back-office) and use those instead.

Type Directory Purpose
Universal invalid arrays test-data/static/util/ Type-mismatch tuples reused by every negative test (.ts, as const)
Domain-specific static test-data/static/{area}/ Curated invalid/boundary sets tied to the app's validation rules (.ts, as const)
Dynamic factories test-data/factories/{area}/ Faker + Zod factories for unique, valid data per test run

Read the full file on GitHub · 232 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 · 232 lines · 2,684 tokens per session scan A 5637b1186f40

Subscribe to this mod's changes

agentic-playwright data-strategy.instructions.md is an instructions file published in the GitHub repository idavidov13/agentic-playwright (134 stars, last pushed 5d ago), licensed MIT. It adds 2,684 tokens to every session, about $0.0134 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 2026-08-30.