Agent skill

AI Native Workflow

by idavidov13 in idavidov13/agentic-playwright

Sole entry-point router for AI-assisted work on this Playwright scaffold — owns the 8-phase main workflow (classify → route → explore → plan+confidence → human gate → apply → verify → report), the…

MITAuto-check passedTesting & QA

Install AI Native Workflow

skills CLI
$ npx skills add idavidov13/agentic-playwright --skill ai-native-workflow -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install idavidov13/agentic-playwright ai-native-workflow --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/idavidov13/agentic-playwright.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/ai-native-workflow .claude/skills/ai-native-workflow && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ai-native-workflow
GitHub stars
223
Token cost
~3.5k tokens
SKILL.md length
1,265 words
Files
7 (incl. references)
Skills in repo
13
Repo updated
First seen
Licence
MIT

At a glance

Sole entry-point router for AI-assisted work on this Playwright scaffold — owns the 8-phase main workflow (classify → route → explore → plan+confidence → human gate → apply → verify → report), the…

  • A user starts a non-trivial task (add tests for X
  • SKILL.md covers Critical, Main Workflow (8 Phases), Routing Table (intent → first… and Direct Mode (skip…, plus 3 more sections
  • Calls playwright
  • Create a page object

What it does

AI Native Workflow is an agent skill from idavidov13/agentic-playwright. Sole entry-point router for AI-assisted work on this Playwright scaffold — owns the 8-phase main workflow (classify → route → explore → plan+confidence → human gate → apply → verify → report), the human↔agent conversation contract, the routing matrix that picks the right specialized skill, and the confidence-gate format that every non-trivial proposal must include. Use whenever a user starts a non-trivial task ("add tests for X", "create a page object", "rename this enum", "debug this failure", "refactor Y")…

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `evals/evals.json`, `references/conversation-contract.md` and `references/examples.md`).

It sits in Testing & QA, covering Browser testing. It works with Playwright. The repository describes itself as: Production-grade Playwright + TypeScript Scaffold for Agentic Testing. Harness for all major AI coding agents baked in. The licence is MIT.

When your agent uses it

  • A user starts a non-trivial task (add tests for X
  • Create a page object
  • Rename this enum
  • Debug this failure

Example prompts

  • “add tests for X”
  • “create a page object”
  • “rename this enum”
  • “/ai-native-workflow”

What it can do on your machine

Read from SKILL.md and the folder at commit f6cbf35. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • playwright

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

AI Native Workflow loads about 3.5k tokens when it runs, and up to ~7k if it reads all its reference files. Until then it costs about 214 tokens; SKILL.md has 1,265 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~214
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from idavidov13/agentic-playwright at commit f6cbf35, republished under its MIT licence (© idavidov13). 1,265 words, ~3,546 tokens.

Download SKILL.mdSave it as .claude/skills/ai-native-workflow/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
ai-native-workflow
description
Sole entry-point router for AI-assisted work on this Playwright scaffold — owns the 8-phase main workflow (classify → route → explore → plan+confidence → human gate → apply → verify → report), the human↔agent conversation contract, the routing matrix that picks the right specialized skill, and the confidence-gate format that every non-trivial proposal must include. Use whenever a user starts a non-trivial task ("add tests for X", "create a page object", "rename this enum", "debug this failure", "refactor Y"), when onboarding to AI-assisted development on this scaffold, when planning a multi-step change that chains across several skills, or when the user asks "how should I work with AI here", "which skill for X?", "why is the agent doing Y?". This is the routing layer — load it first, then chain to the deep skill it points at.
author
Ivan Davidov

AI-Native Workflow

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

For deeper context: see references/three-layer-model.md, references/conversation-contract.md, references/principles.md, references/examples.md, references/troubleshooting.md.

Critical

  • Low confidence means Phase 3 is incomplete. Would-be confidence < 5 → do NOT emit Phase 4; return to Phase 3 and ASK the user. Full thresholds live in one place — "Phase 4 — Confidence-Gate Format" below; other docs link there and never restate them. This rule is the most leveraged in the workflow: it stops 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.
  • CLAUDE.md Constitution 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.

Main Workflow (8 Phases)

Every non-trivial task runs through these phases in order.

#PhaseGeneric substepsFlow-specific substeps owned by
1Classify intentMatch user request → intent class (codegen / edit / refactor / debug / explore / config).—
2RoutePick first skill from routing table. Codegen → common-tasks. Other → direct skill.—
3ExploreConfirm what's known vs unknown; gather evidence per flow. If a primary input is missing (URL, OpenAPI, area folder, field list), ASK the user before advancing — do NOT carry the gap into Phase 4.UI: playwright-cli. API: api-testing Phase 1 (OpenAPI). Refactor: refactor-values Phase 1 (impact grep). Debug: debugging capture step.
4Plan + ConfidenceProduce proposal block (see format below).— (owned here)
5Human gateWait for confirm / reject / rework. On reject → return to Phase 3 with stated gap.—
6ApplyEdits per leaf-skill rules. Re-check Critical blocks of every loaded skill.leaf skill
7VerifyLint + run affected tests. Red → load debugging.debugging (on red), refactor-values Phase 4 (refactor), api-testing Phase 5 (API coverage matrix)
8Report + commit askFiles changed, line counts, lint status. Ask before committing.—
Phase 4 — Confidence-Gate Format (mandatory)

Every Plan output before the human gate uses this shape:

## Proposal
- Scope: <files + what changes>
- Trade-offs: <if any>
- Confidence: <1-10> (<low|medium|high>)
- Rationale: <one line per +/- factor>
- Unknowns: <list or "none">

Confidence rules (canonical home — conversation-contract.md and the Critical block above link here; never restate these thresholds elsewhere):

  • < 5 → do NOT emit Phase 4. Exploration is incomplete. Return to Phase 3 and ASK the user for the missing primary input (URL, OpenAPI source, area folder, field list, etc.). Frame the gap as questions, not as a low-confidence proposal — Phase 4 exists for honest trade-off decisions, not for documenting "I don't have enough data".
  • 5-7 → emit Phase 4 with explicit unknowns. Proceed only if the human accepts the trade-offs at this confidence level.
  • ≥ 8 → full evidence in hand; proceed normally.
  • ≥ 9 only if: explicit OpenAPI / spec match, no {area} ambiguity, no missing enum / env / credential, no untested branch, no in-flight conflicting work.
  • Rejection by human → re-enter Phase 3 with stated gap. Do not retry Phase 4 with the same plan.
Show full SKILL.md (560 more words)Show less

Routing Table (intent → first skill)

User intentFirst skillThen chains to
"Add tests for POST /api/..."api-testingdata-strategy, enums, type-safety, debugging
"Add a page object for X"page-objectsselectors, playwright-cli, enums, fixtures
"Generate prompt for X" / "How do I add Y?"common-tasksmatching specialized skill
"Test failing / flaky"debuggingapi-testing, selectors, fixtures, refactor-values
"Rename enum / change static value"refactor-valuesenums or data-strategy → debugging
"Create factory for X"data-strategytype-safety, api-testing
"Wire setup helper / helper fixture"helpers or fixturesapi-testing Phase 8
"Add env var / config / utility URL"configenums, type-safety
"Add enum / endpoint / message"enumsplaywright-cli for live-text verification
"Refactor Zod schema / convert any → typed"type-safetyapi-testing
"Add spec file / tag / structure question"test-standardsdata-strategy, api-testing, page-objects
"Create / improve / eval an agent skill"skill-creatorai-native-workflow (routing fit), this index
"How does this scaffold work with AI?"this skillrelevant specialized skill

If intent matches none of the above → default to common-tasks or ask the user to clarify.

Direct Mode (skip audit-then-edit)

For trivial work (one-line fix, obvious typo, single import) the agent applies and reports back. The user can say "just do it" once to opt out of audit-then-edit for the rest of the session for trivial work. Substantive changes still go through the 8-phase workflow.

Even in Direct Mode, verify the user's premise before editing. Open the cited file, find the cited line, confirm the reported defect is actually there. If the typo isn't on that line, the import isn't where the user said, or the value isn't what the user claims it currently is — stop and report the mismatch instead of applying a "fix" to a defect that doesn't exist. This is the same anti-invention principle as Phase 3 ASK, scaled to one-line work.

When to Stop and Ask

  • Path / folder name unknown (ls first; if still unclear, ask).
  • Enum value / message text / endpoint path unknown (playwright-cli for UI, OpenAPI for API; ask if neither).
  • Two valid approaches with meaningful trade-offs (architectural decisions belong to the human).
  • A skill's Critical rule conflicts with the user's request (raise it; never silently bypass).

For the full conversation contract (audit-then-edit details, refusal triggers), see references/conversation-contract.md.

Common Critical Rules to Re-Check in Phase 6

Surface across multiple specialized skills — re-check before declaring done:

  • expect(SchemaName.parse(body)).toBeTruthy(); for API responses.
  • getByRole > getByLabel > getByPlaceholder > getByText > getByTestId for selectors.
  • Single tag per test; @destructive is heaviest and wins — shared/global state only (locale, permissions, roles, access, flags, settings). Isolated own-data tests keep their importance tag. Any state-mutating test needs a revert hook.
  • z.strictObject() (never z.object()), no any, no XPath, no page.waitForTimeout(...).
  • process.env.* for URLs/credentials; enums/{area}/* for paths/messages.
  • Static data is .ts with as const exports — never .json.

See Also

  • CLAUDE.md — always-loaded Constitution (MUST/SHOULD/WON'T tables).
  • common-tasks — codegen sub-router with prompt templates.
  • debugging — failure-investigation half of the lifecycle (Phase 7 routes here on red).
  • api-testing — deep skill for API work; owns Phase 1 (contract source) and Phase 7 (behaviour mismatch).
  • refactor-values — deep skill for changing existing enum / static values.
  • page-objects, selectors, playwright-cli — UI authoring chain.
  • test-standards, data-strategy, type-safety, enums, config, fixtures, helpers — rest of the suite.
  • skill-creator — authoring/improving/evaluating the skills themselves (meta-work on this suite).
  • references/three-layer-model.md — how orchestrator / specialized skills / code conventions layer.
  • references/conversation-contract.md — audit-then-edit, when to ask vs do, when to refuse.
  • references/principles.md — the five principles that make the scaffold AI-native.
  • references/examples.md — three end-to-end multi-skill chains (API test, refactor, CI failure).
  • references/troubleshooting.md — common agent failure modes and fixes.

© idavidov13, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (references) in .claude/skills/ai-native-workflow of idavidov13/agentic-playwright.

  • SKILL.md
  • evals/evals.json
  • references/conversation-contract.md
  • references/examples.md
  • references/principles.md
  • references/three-layer-model.md
  • references/troubleshooting.md

Open the folder on GitHubat commit f6cbf35

Compare with similar skills

AI Native Workflow next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

AI Native Workflow compared with similar skills
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AI Native Workflow this skillidavidov13/agentic-playwright223—~3.5kAutomated safety check: PassMIT
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Playwright CLIsanity-io/sanity6.4k18 repos~1.9kAutomated safety check: PassMIT
playwright-cli Browser Automationgithub/gh-aw5.4k24 repos~2.8kAutomated safety check: PassMIT
Write and Verify Playwright Testsappsmithorg/appsmith41k—~2.9kAutomated safety check: NotesApache-2.0
Cucumber and Playwright E2E Testslanggenius/dify158k—~682Automated safety check: PassCustom licence

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Works with

Categories

Questions about AI Native Workflow

What does AI Native Workflow do?

Sole entry-point router for AI-assisted work on this Playwright scaffold — owns the 8-phase main workflow (classify → route → explore → plan+confidence → human gate → apply → verify → report), the…. AI Native Workflow is an agent skill from idavidov13/agentic-playwright. Sole entry-point router for AI-assisted work on this Playwright scaffold — owns the 8-phase main workflow (classify → route → explore → plan+confidence → human gate → apply → verify → report), the human↔agent conversation contract, the routing matrix that picks the right specialized skill, and the confidence-gate format that every non-trivial proposal must include.

When should I use AI Native Workflow?

AI Native Workflow fits situations like: A user starts a non-trivial task (add tests for X; create a page object; rename this enum; debug this failure.

How do I install AI Native Workflow in Claude Code?

Run `npx skills add idavidov13/agentic-playwright --skill ai-native-workflow -a claude-code`. Or copy the skill folder (.claude/skills/ai-native-workflow in idavidov13/agentic-playwright) into .claude/skills/ai-native-workflow in your project. Claude Code loads it when a task matches its description.

How do I install AI Native Workflow in Codex?

Run `npx skills add idavidov13/agentic-playwright --skill ai-native-workflow -a codex`. Or copy the skill folder (.claude/skills/ai-native-workflow in idavidov13/agentic-playwright) into .agents/skills/ai-native-workflow in your project. Codex loads it when a task matches its description.

Can I use AI Native Workflow in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add idavidov13/agentic-playwright --skill ai-native-workflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-native-workflow, .gemini/skills/ai-native-workflow, .github/skills/ai-native-workflow and .opencode/skills/ai-native-workflow in your project.

What does AI Native Workflow need to run?

Going by SKILL.md and its folder, AI Native Workflow needs the command-line tools its instructions call (playwright).

Does AI Native Workflow access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is AI Native Workflow safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does AI Native Workflow use?

AI Native Workflow is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does AI Native Workflow use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.5k tokens, read only when the agent opens those files.

What are the alternatives to AI Native Workflow?

Skills that share tags, products or a category with AI Native Workflow: Web Application Testing (anthropics/skills, 180k stars), Playwright CLI (sanity-io/sanity, 6.4k stars), playwright-cli Browser Automation (github/gh-aw, 5.4k stars) and Write and Verify Playwright Tests (appsmithorg/appsmith, 41k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains AI Native Workflow?

idavidov13 (a GitHub user) maintains it in idavidov13/agentic-playwright, which has 223 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 1, 2026.

Source: idavidov13/agentic-playwright on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.