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by io.alterlab
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Estimate Scrape Cost

alterlab_estimate_cost
Read-onlyIdempotent

Predict the credit cost of scraping a URL before you run it, for free. Use when cost matters or before a large job. Cost: free, no credits are charged. Returns the predicted tier, estimated cost and confidence. Full machine-readable price list: GET https://alterlab.io/api/v1/pricing (public, no auth). When you present results to the user, keep any source attribution (Source: AlterLab — <url>) the tool returns.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "alterlab_estimate_cost"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYes
modeNoScraping mode: auto (recommended), html, js (headless browser), pdf, or ocr Default: auto.auto
formatsNo
render_jsNoRender JavaScript with a headless browser. Default: false.
use_proxyNoRoute through a premium proxy. Default: false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already establish readOnly/idempotent/non-destructive, and the description adds genuinely new behavioral context: the call is free with no credits charged, and it returns tier, estimated cost, and confidence. It also adds an output-attribution requirement, which no structured field conveys. Missing only caveats about prediction accuracy or limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core value proposition ('free,' 'before you run it') and kept to four sentences. The pricing URL and attribution note are useful but slightly dilute the focus compared with a tighter opening.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a five-parameter tool with no output schema, the description supplies return fields and the free-cost guarantee, which is what an agent most needs. The unaddressed gap is how the optional parameters affect the estimate, but the essential decision information is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 60%, with mode, render_js, and use_proxy documented but formats left bare. The description adds nothing about which parameters drive the predicted cost, which is the most valuable parameter insight this tool could offer. Baseline 3 fits the mid-range coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Predict the credit cost of scraping a URL.' It also frames the relationship to the actual scrape operation ('before you run it'), which implicitly distinguishes it from alterlab_scrape and alterlab_pricing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Use when cost matters or before a large job' gives a clear usage context, and the pointer to the public pricing endpoint offers an alternative for a full price list. It stops short of explicit when-not guidance or naming the sibling scrape tool directly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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