agentic-playwright ai-native-workflow.instructions.md

A routing guide for an eight-phase workflow that turns a coding request into verified implementation steps. It emphasizes checking primary inputs, such as URLs, API contracts, field lists, and project folders, before generating code.

In plain words
What is it for?
Use it at the start of a non-trivial Playwright task to classify the request, gather project facts, choose specialized instructions, assess confidence, and plan verification.
Why use it?
It prevents plausible-looking plans built on guesses and stops the agent when important information is missing. It also provides a confidence gate for deciding whether to proceed or ask the user for details.

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/ai-native-workflow
Clone the repo
git clone --depth 1 https://github.com/idavidov13/agentic-playwright

Made for: GitHub Copilot.

Per session 2,744 This file is loaded in full into every session.
When invoked 2,744 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 $0.02744 $0.02744
Opus 5 $0.01372 $0.01372
Sonnet 5 $0.00549 $0.00549
Haiku 4.5 $0.00274 $0.00274

Measured 2d ago against content hash 5689f358c3e3, 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 ai-native-workflow.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/ai-native-workflow.instructions.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI-Native Workflow

Routing layer between user intent and the specialized skills that own the rules. Load first on every non-trivial task.

Critical

  • Low confidence means Phase 3 is incomplete. If the would-be confidence is < 5, do NOT emit Phase 4. Return to Phase 3 and ASK the user for the missing primary inputs (URL, OpenAPI link, field list, area name). Phase 4 exists for honest trade-off decisions, not for documenting "I don't have enough data" — that belongs in a question to the user. This rule is the most leveraged in the workflow: it is what stops the agent from emitting plausible-looking plans built on guesses.
  • Ask, don't invent. Never guess folder names, file paths, env-var names, enum values, credentials, or message strings. ls, grep, playwright-cli, OpenAPI — or ask.
  • Refuse placeholders. Guessed selectors, unverified message strings, made-up enum values, secret-shaped strings — refuse and re-explore. TODO / skeleton / "to fill in later" outputs count as placeholders too — offering a "skeleton page object with TODO locators while we wait for playwright-cli" is the same failure mode as inventing locators outright; don't.
  • Verify the user's premise even in Direct Mode. Before applying a one-line fix, confirm the reported defect actually exists (the typo on the cited line, the import the user wants removed, the value the user says is currently set). If the premise doesn't match the file, switch out of Direct Mode and ASK — applying a "fix" to a defect that isn't there invents a change.
  • Specialized skills own the rules. This skill never restates rules from api-testing, page-objects, etc. It tells you which skill to load and in what order.
  • The Constitution (the always-on instructions wrapping these skills) is the safety floor. MUST/SHOULD/WON'T tables are hard stops; they take precedence over any prose, template, or example.
  • Audit-then-edit by default. For any non-trivial change, follow the 8-phase workflow below. Phase 4 (Plan + Confidence) is mandatory before Phase 6 (Apply).
  • Confidence gate is required. Every Plan output must include a 1-10 confidence + rationale + unknowns block. See "Phase 4" below.
  • Exploration is non-negotiable. UI → playwright-cli only (no IDE browser MCP, no Cursor browser, no playwright codegen). API → OpenAPI/docs first, live HTTP only as fallback.
  • One skill at a time. Load skills sequentially per the routing table. Don't stack 5 skills' Critical blocks before starting work.
  • After any test edit, run the affected tests. On red, load debugging — never suppress, never bump timeouts.

Read the full file on GitHub · 119 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 · 119 lines · 2,744 tokens per session scan A 5689f358c3e3

Subscribe to this mod's changes

agentic-playwright ai-native-workflow.instructions.md is an instructions file published in the GitHub repository idavidov13/agentic-playwright (139 stars, last pushed 5d ago), licensed MIT. It adds 2,744 tokens to every session, about $0.0137 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.