agentleFS
zznabilzznabil/lean-agent-skill-collection/skills/browser-automation/SKILL.md

browser-automation

Skill1 starsChanged 3 months agoMITView on GitHub

Build or run authorized browser automation, real-user QA, data entry, or extraction with stable locators, explicit state, bounded retries, and evidence of the user-visible result.

53 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use karpathy-coder, api-test-suite-builder and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • csiddhant796-blipSkill

    karpathy-coder

    Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on "review my diff", "check complexity", "am I overcomplicating this", "karpathy check", "before I commit", or any code quality concern where the LLM might be overcoding.

    Also in 5 projects that use this

  • Arnav-0Skill

    api-test-suite-builder

    Use when the user asks to generate API tests, create integration test suites, test REST endpoints, or build contract tests.

    Also in 6 projects that use this

  • Hussain-ElfalahSkill

    andreessen

    Also in 4 projects that use this

  • Hussain-ElfalahSkill

    business-investment-advisor

    Also in 4 projects that use this

  • csiddhant796-blipSkill

    self-eval

    Honestly evaluate AI work quality using a two-axis scoring system. Use after completing a task, code review, or work session to get an unbiased assessment. Detects score inflation, forces devil's advocate reasoning, and persists scores across sessions.

    Also in 5 projects that use this

  • DorianGalloSkill

    binary-diff

    跨版本符号迁移与二进制差分。当你有旧版本的符号/逆向结果,需要快速迁移到新版本时使用。 适用场景:内核缺 PDB 用旧版符号推导、程序更新后批量迁移函数名、应用更新后快速定位新偏移。 核心方法:用 LLM 做结构化差异比对,程序化输入输出,成本极低(200 函数 ~1 元)。 触发关键词:符号迁移、bindiff、跨版本、PDB 缺失、函数偏移迁移、symbol migration、binary diff、版本对比。

    Also in 5 projects that use this

  • +1 more from Hussain-Elfalah

The file

We split this skill into the rules it gives an agent

10 rules. 0 are common, 10 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 36 edited versions we read keep these.

  • 10

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Prefer native semantics to custom ARIA.

    line 8
  2. Distinctive:

    Session isolation: Use an isolated profile or clean context by default.

    line 15
  3. Distinctive:

    Recovery and resumption: Start critical journeys from known state.

    line 17
  4. Distinctive:

    Locators and read-back: Use semantic or stable locators and small actions.

    line 18
  5. Distinctive:

    When the scope includes interactive accessibility, verify keyboard operation, focus order, accessible name, role, state, and visible result.

    line 20
  6. Distinctive:

    Do not bypass access controls, anti-abuse systems, CAPTCHA, or consent.

    line 26
  7. Distinctive:

    Use ASD-STE100-inspired short, active technical sentences and familiar words.

    line 29
  8. Distinctive:

    Use BCP 14 only for normative force.

    line 33
  9. Distinctive:

    Before risky or failure-prone work, warn, add any needed hold point and verify the safe state.

    line 34
  10. Distinctive:

    Avoid surprise scope; leave results usable or resumable.

    line 36

“Common” is measured: kept by at least 6 in 10 of the 36 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Browser Automation

For applicable interfaces, use WCAG 2.2, WAI-ARIA Authoring Practices, and ISO 9241-110/210. Use current ISO 9241-112:2025 information-presentation principles and ISO 9241-171:2025 software-accessibility guidance.

  • Apply ISO/IEC 23859:2023, ISO 21801-1:2020, and ISO/IEC 29138-1/-4 when UI text, cognition, or user accessibility needs can block the task.
  • Prefer native semantics to custom ARIA.

Composition

For a composed task, use one primary lifecycle owner: the explicit user-designated owner; otherwise selected get-it-done; otherwise the unique substantive task skill after assigning support roles. If ownership is still ambiguous, stop affected actions and report the competing claims. The named owner MUST be available, selected and loaded before composed execution; otherwise stop its dependent actions and report the missing prerequisite. Safe independent inspection may continue. Availability alone proves neither selection nor loading. Alone, this skill retains its normal ownership and status rules. When supporting, execute only authorized browser journeys and return per-journey evidence and verdicts, not task completion. Quick Mode chooses the minimum useful validation within retained criteria. Source, compilation and uninteracted screenshots are not dogfooding. Automated UAT requires a known start, user-level actions, observable failure-sensitive assertions, replayable execution and cleanup/reset; a one-off interaction is not repeatable UAT. For automated UAT, pass a positive control and reject a representative broken state before claiming the verifier works. Mandatory safety, trusted repository policy, authorization and explicit acceptance criteria take precedence over role defaults. A supporter MUST NOT claim task completion or change permissions. Preserve failed verdicts and missing required evidence in the owner's single final report; neither permits accepted completion. Presentation changes no facts, scope or verdicts.

  1. Authority and journey. Name the authorised site, account, environment, intended users, user-visible result, journeys and allowed side effects. Trace material accessibility barriers as user accessibility need → barrier → journey or requirement → evidence.
  2. Session isolation. Use an isolated profile or clean context by default. Use a real signed-in profile only when required and authorised. Do not copy cookies, tokens or unrelated session data.
  3. Runtime and readiness. Establish the runtime path and start permitted local services. Inspect the rendered page, accessibility tree or screenshot before selecting locators. Wait for meaningful readiness, not a fixed sleep.
  4. Recovery and resumption. Start critical journeys from known state. Where recovery or persistence matters, test reload, reopen, stale state, session expiry and interruption. Verify that returning users can identify completed, current and pending work, with important input preserved.
  5. Locators and read-back. Use semantic or stable locators and small actions. Verify navigation or mutation through visible state, DOM, accessibility tree, network, console, saved files, screenshots or target-system read-back.
  6. Interaction and accessibility. Across representative viewports or window sizes, exercise the few states most likely to fail: loading, empty, error, disabled, focus, resize, invalid input, slow or failed network, cancellation, and recovery.
    • When the scope includes interactive accessibility, verify keyboard operation, focus order, accessible name, role, state, and visible result.
    • For important UI text or errors, verify that the user can identify the purpose, next action, expected result, and whether the system preserved work or data.
  7. Retry boundary. Retry only known transient failures. Record intent before a consequential submission. If the result is uncertain, inspect state before retrying.
  8. Rendered evidence. Capture concise, reproducible evidence without secrets. For reference-driven interface work, compare rendered output side by side or with an overlay. Fix the largest meaningful mismatch first. Source inspection does not prove that a user journey works.
  9. Regression guard. Convert durable behavior observed manually into the smallest regression test. Use semantic locators and an outcome assertion.
  10. Journey verdict. Report PASS, FAIL, or BLOCKED for each independent journey. Include the environment and evidence. Do not bypass access controls, anti-abuse systems, CAPTCHA, or consent. Do not purchase, publish, send, delete, or mutate production without explicit authorization.

Communication kernel

Number ordered actions; group long lists without hiding required items. After interruption or task change, restore relevant completed/current/pending state, not repetitive status each turn. Preserve language, exact tokens, formats, permissions and evidence. Never invent estimates or diagnose readers. Show verified outcomes and factual errors; give a concrete next action only if work remains. - If trusted root AGENTS.md loads, its policy governs. Otherwise apply this standalone kernel. Do not claim root activation without evidence.

  • Use ASD-STE100-inspired short, active technical sentences and familiar words. Use ISO 704-inspired stable concepts and terminology. Use Diátaxis to separate how-to, reference, and explanation when useful. These are the default communication drivers, not a claim of formal standards conformance.
  • Lead with the supported result, action or blocker. Report fresh verification, material uncertainty and remaining user action. Omit routine tool narration and praise.
  • State verified failure and evidenced responsibility directly. Correct actual agent errors or give the next safe action.
  • Preserve facts, negation, uncertainty, evidence limits, permissions, quotations, requested voice and exact artefact formats.
  • Use BCP 14 only for normative force. Important requirements name one actor, action and observable check; do not turn advice into mandates.
  • Before risky or failure-prone work, warn, add any needed hold point and verify the safe state. State the expected result, failure sign and recovery. Explain difficult mechanisms simply; use compliant/noncompliant contrasts only when useful.
  • For measurable multi-step work with a defensible total, show named 20-cell ASCII progress, rounded down from processed items, separately from the verdict. Processed does not mean passed. Otherwise report phase and evidence.
  • Avoid surprise scope; leave results usable or resumable. Keep simple replies short without truncating needed detail. Omit routine Summary headings and closing recaps. Use TL;DR only when helpful for a complex response, and place it first.

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