Tabstack — Web & PDF Tools for AI Agents

Tabstack is a web execution API for reading, extracting, transforming, and
interacting with web pages and PDF documents. It handles JavaScript-rendered
sites, structured data extraction, AI-powered content transformation, and
multi-step browser automation.

Setup (first use only)

Install dependencies from the skill's directory:

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Where <skill-dir> is the directory containing this SKILL.md file.

Operations

All operations are run via the exec tool. First cd into the skill directory,
then run the command with a relative path:

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Execution strategy: Always run tabstack commands in the foreground —
call exec and wait for completion. Background execution requires manual
polling and is unreliable.

JSON arguments: Any JSON argument (schema, --data) can be passed inline
or as a file path prefixed with @ (e.g. @/tmp/schema.json). Use file
paths for complex schemas to avoid shell quoting issues.

1. extract-markdown — Read a page or PDF as clean Markdown

Best for: reading articles, documentation, PDF reports. This is the cheapest
operation — prefer it when you just need to read content.

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Returns the page/PDF as Markdown. For web pages, includes YAML frontmatter
metadata (title, author, etc.).

Optional flags:

• - --metadata — return metadata as a separate JSON block
• INLINECODE8 — bypass caching and get fresh content
• INLINECODE9 — fetch from a specific country (ISO 3166-1 alpha-2, e.g. US, GB)

2. extract-json — Pull structured data from a page or PDF

Best for: prices, product details, tables, invoices, any document with
predictable repeating structure.

Without a schema (Tabstack infers structure):
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With a JSON Schema (inline or from file):
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Optional flags: --nocache, --geo CC.

See references/examples.md for common JSON schema
patterns (products, articles, events, tables, contacts).

3. generate — Transform web/PDF content into a custom JSON shape

Best for: summaries, categorization, sentiment analysis, reformatting. Unlike
extract-json (which pulls existing data), generate uses an LLM to create
new content. May be slower due to LLM processing.

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Optional flags: --nocache, --geo CC.

Example — categorise and summarise HN posts:
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See references/examples.md for more schema and
instruction examples.

4. automate — Multi-step browser task in natural language

Best for: tasks needing real browser interaction — clicking, navigating across
pages, filling forms. Does NOT support PDFs or --geo.

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Optional flags:

• - --url <url> — starting URL for the task. When omitted, automate uses its

own built-in web search to find relevant pages — this can be cheaper and
faster than research for simple factual questions.

• - --max-iterations N — limit steps (default 50, range 1-100)
• INLINECODE25 — safety constraints (e.g. "browse only, don't submit forms")
• INLINECODE27 — JSON context for form filling

Timeout: May take 30-120 seconds. Use at least 420s exec timeout.

Example — fill a contact form with guardrails:
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Example — simple search (no URL, uses built-in web search):
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5. research — AI-powered deep web research

Searches the web, analyzes multiple sources, and synthesizes a comprehensive
answer with citations. Unlike the other operations, research doesn't need
a URL — you give it a question and it finds the answers.

For simple factual lookups, automate without a --url may be faster and
cheaper. Use research when you need depth, multiple perspectives, or
cited sources.

Use cases:

• - Complex questions that need multiple sources ("What are the pros and cons

of Rust vs Go for CLI tools?")

• - Fact-checking and verification ("Is it true that...")
• Current events and recent information
• Topic deep-dives and literature reviews
• Competitive research ("Compare X vs Y vs Z")

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Optional flags:

• - --mode fast|balanced — fast for quick single-source answers, INLINECODE35

(default) for deeper multi-source research with more iterations

• - --geo CC — research from a specific country's perspective

Timeout: May take 60-120 seconds. Use at least 420s exec timeout.

Example — quick factual lookup:
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Example — deep research:
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Reference: Examples & Recipes

Read references/examples.md when you need to:

• - Build a JSON schema for extract-json — patterns for products, articles,

events, tables, contacts, invoices

• - Write effective instructions for generate — recipes for summarization,

sentiment analysis, competitive analysis, content digests

• - Recover from a failed attempt — if a command doesn't produce good

results, check for a better approach

Choosing the Right Operation

Operation	Use when...	Cost	Timeout
INLINECODE39	Read/summarise a page or PDF	Lowest	60s
INLINECODE40

Structured data from a page or PDF | Medium | 60s | | generate | AI-transformed content from a page or PDF | Medium | 60s | | research | Answers from multiple web sources | Medium | 420s | | automate | Browser interaction or simple web search (no PDF) | Highest | 420s |

Prefer cheaper operations when they suffice. Use extract-markdown for
simple reading. Only use automate when the task requires clicking,
navigating, or form interaction.

Inform the user before triggering multiple automate calls — they are the
most expensive.

Error Handling

Error	Meaning
INLINECODE47	TABSTACKAPIKEY is missing or invalid
INLINECODE48

URL is malformed or page is unreachable | | 400 Bad Request | Malformed request — check arguments | | No output | Task timed out or page blocked automation |

On automate failures, retry once. If it fails again, fall back to
extract-markdown for read-only tasks.

Environment Configuration

This skill requires a TABSTACK_API_KEY to function. Get one from
tabstack.ai (Mozilla-backed, free tier available).

Set the key via the CLI:

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The skill will exit with an error if the key is not set.

Security & Privacy

• - API key: This skill requires a TABSTACK_API_KEY. All requests are

sent to the Tabstack API (api.tabstack.ai) using this key for authentication. The key is read from the environment, not hardcoded.

• - Data sent to Tabstack: URLs you process, JSON schemas, instructions,

and any --data payloads are sent to Tabstack's servers for processing. Do not pass passwords, authentication tokens, or other secrets via --data unless you explicitly trust the Tabstack service.

• - Browser automation: The automate command drives a remote browser

that can click, navigate, fill forms, and submit data. Use --guardrails to constrain what the browser can do (e.g. "browse only, don't submit forms").

• - Dependencies: This skill installs @tabstack/sdk and tsx from npm.

A package-lock.json is provided for reproducible installs.

• - No persistence: The skill does not modify agent configuration, store

credentials, or run outside of its own directory.