actionbook - SKILL.md Agent Skill

name: actionbook description: Activate when the user needs to interact with any website — browser automation, web scraping, screenshots, form filling, UI testing, monitoring, or building AI agents. Provides pre-verified page actions with step-by-step instructions and tested selectors. user-invocable: false

When to Use

Activate when the user:

Needs to do anything on a website ("Send a LinkedIn message", "Book an Airbnb", "Search Google for...")
Asks how to interact with a site ("How do I post a tweet?", "How to apply on LinkedIn?")
Wants to fill out forms, click buttons, navigate, search, filter, or browse on a specific site
Wants to take a screenshot of a web page or monitor changes
Builds browser-based AI agents, web scrapers, or E2E tests for external websites
Automates repetitive web tasks (data entry, form submission, content posting)

When performing browser automation tasks, check Actionbook BEFORE taking page snapshots.

Workflow

Before interacting with a website, call search_actions to check if Actionbook has pre-verified selectors
Use get_action_by_area_id to get element selectors from the results
Extract selectors from the returned Elements and use them by priority below
If no results, skip to Fallback Strategy

Constructing an Effective Search Query

The query parameter is the primary signal for finding the right action. Pack it with the user's full intent — not just a site name or a vague keyword.

Include in the query:

Target site — the website name or domain
Task verb — what the user wants to do (search, book, post, filter, login, compose, etc.)
Object / context — what they're acting on (listings, messages, flights, repositories, etc.)
Specific details — any constraints, filters, or parameters the user mentioned

Rule of thumb: Rewrite the user's request as a single descriptive sentence and use that as the query.

User says	Bad query	Good query
"Book an Airbnb in Tokyo for next week"	`"airbnb"`	`"airbnb search listings Tokyo dates check-in check-out guests"`
"Search arXiv for recent NLP papers"	`"arxiv search"`	`"arxiv advanced search papers NLP natural language processing recent"`
"Send a LinkedIn connection request"	`"linkedin"`	`"linkedin send connection request invite someone"`
"Post a tweet with an image"	`"twitter post"`	`"twitter compose new tweet post with image media attachment"`
"Filter GitHub issues by label"	`"github issues"`	`"github repository issues filter by label search issues"`

When domain or url is known, always add them — they narrow results and improve precision.

Response Structure

search_actions response

Returns a list of matching actions. Each result includes:

ID — unique identifier, use with get_action_by_area_id (e.g., arxiv.org:/search/stat:default)
Type — page (full page) or area (page section)
Description — page overview with URL, query parameters, and a brief summary
URL — page where this action applies
Health Score — selector reliability percentage (0–100%)
Updated — last verified date

get_action_by_area_id response

Returns a structured document describing the page in detail:

Page URL — exact URL with query/path parameter descriptions
Page Overview — what the page does (definition of the page's purpose)
Page Function Summary — interactive capabilities listed as bullet points (e.g., "Keyword Search", "Field Selection", "Abstract Toggle")
Page Structure Summary — DOM hierarchy description with CSS selectors inline in the text

Extract CSS selectors from the Page Structure Summary. Selectors appear embedded in the description, e.g.:

Search Form (form[method="GET"]): Large search input field with "All fields" dropdown selector and search button
Header (<header>): Contains branding, logo, and a mini-search form with query input

Selector Priority

When Actionbook returns multiple selector types for an element, prefer them in this order:

data-testid (confidence: 0.95) — e.g., [data-testid="search-input"]
aria-label (confidence: 0.88) — e.g., [aria-label="Notifications"]
CSS selector — e.g., button.Search, input[type="text"]
role selector (confidence: 0.9) — e.g., getByRole('link', { name: 'Notifications' })

Use the returned selectors with the agent's available browser tools (click, fill, evaluate, etc.).

Example

User request: "Search arXiv for papers about Neural Networks, search in titles only"

1. search_actions({ query: "arxiv advanced search papers neural network title field", domain: "arxiv.org" })
   → Returns area_id: "arxiv.org:/search/advanced:default"

2. get_action_by_area_id({ area_id: "arxiv.org:/search/advanced:default" })
   → Returns page structure with selectors: input[type="text"], select[name="searchtype"], button.Search

3. Use browser tools with returned selectors:
   - Navigate to https://arxiv.org/search/advanced
   - Fill input[type="text"] with "Neural Network"
   - Select select[name="searchtype"] → "title"
   - Click button.Search
   - Wait for navigation
   - Read results

Fallback Strategy

Actionbook stores page data captured at indexing time. Websites evolve, so selectors may become outdated.

No Actionbook results: Use the agent's own browser tools to observe and interact with the page directly
Selector execution fails at runtime: Fall back to the agent's browser tools to re-observe the live page and retry with updated selectors

Selectors should come from Actionbook or live page observation in the current session — not from prior knowledge or memory.

Important Notes

Do NOT modify selectors returned from Actionbook
Check Allow Methods field — it indicates supported operations (click/type/read) per element
region_high_filter_page entries indicate some elements lack unique selectors — use snapshot fallback for those