DeepScout

Add and analyze a website

scout_analyze_website

Add a website to a project: analyze it and scrape a free sample of its products. Each customer has free analyses each month. After them, an analysis charges the prepaid balance when the job is created, without an approval. scout_get_balance shows the free analyses left and the price of one. If none are left, confirm the price with the user before you call this tool. Returns the setup job; poll it with scout_get_job(job_kind="setup") until it is COMPLETED, then check the sample with scout_get_sample. A job that FAILED with the error_code CURRENCY_NOT_AVAILABLE found that the website does not offer the currency: no switch of the website shows its prices in it. The error of the job names the currency the website shows, when the analysis found it. The analysis is used, also a paid one. Ask the user for a currency the website offers, then analyze the website again. A project without localization gets the country and currency of this website.

country: ISO 3166 code of the market to scrape, e.g. "CZ". currency: ISO 4217 code of the prices to scrape, e.g. "CZK".

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>",
      "project_id": "<project_id>",
      "country": "<country>",
      "currency": "<currency>"
    },
    "name": "scout_analyze_website"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes
`country`	Yes
`currency`	Yes
`project_id`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 26, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Annotations only cover openWorldHint and destructiveHint; the description adds the commercially critical behavior that an analysis charges the prepaid balance without approval once free analyses run out, that a failed analysis is still consumed, and that a project without localization inherits this website's country/currency. These are side effects an agent cannot get from structured data and must know before invoking.

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?

Purpose and cost warning are front-loaded, then the job/poll workflow, then error handling, then parameter glossary — a logical order. The CURRENCY_NOT_AVAILABLE paragraph runs long for a single error code, but each sentence carries actionable instruction rather than filler.

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

Completeness5/5

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

For a billing-relevant, job-based mutation, the description covers cost, async lifecycle, polling, sample retrieval, failure semantics, and default localization inheritance. With an output schema present it does not need to describe the returned job payload, and what remains is enough to call and follow through correctly.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate: it defines 'country' as an ISO 3166 market code with the example "CZ" and 'currency' as an ISO 4217 code with "CZK". url and project_id are left to their self-evident names, which is a minor but real gap given none of the four parameters has schema documentation.

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

Purpose4/5

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

States a specific verb+resource ('Add a website to a project: analyze it and scrape a free sample of its products') and scopes it precisely. It distinguishes itself functionally from the scraping siblings, but never names scout_scrape_website or scout_match_websites, so the agent must infer the boundary between adding+analyzing and plain scraping.

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

Usage Guidelines5/5

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

Gives explicit when-to-use routing ('If none are left, confirm the price with the user before you call this tool'), the mandatory follow-up sequence (poll scout_get_job(kind="setup") until COMPLETED, then scout_get_sample), and a concrete recovery path for the CURRENCY_NOT_AVAILABLE failure. Alternatives and exclusions are named rather than implied.

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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