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Tracklution

Scout a website

scout_website
Destructive

Public discovery; works without auth. Detects CMS/platform hints for a public website (fetches it) and creates an onboarding session. Returns onboarding_session_id and a single-use _sensitive_onboarding_session_token: register_and_provision takes both to link this scout to the account and container it creates; get_onboarding_session takes the token before sign-up.

Input Schema

NameRequiredDescriptionDefault
website_urlYesFull URL of the customer's website (http or https).
agent_clientNoWhich AI agent client is calling (cursor, claude-code, lovable, ...).
framework_hintNoOptional framework hint detected by the agent.

Output Schema

NameRequiredDescriptionDefault
dataNo
fieldNo
errorsNo
statusNo
detailsNo
warningsNo
rate_limitNo
http_statusNo
next_actionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedOutput schema / properties / _request_id
      Removed value: -{
      -  "type": "string"
      -}
  2. Added
  3. Removed
  4. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations declare destructiveHint=true and openWorldHint=true, and the description adds genuinely non-obvious behavior: no auth required, a single-use sensitive token, and creation of a persistent onboarding session. It does not address why the call is destructive, whether repeated scouting creates duplicate sessions (idempotentHint=false), or any rate 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?

Three tight sentences, front-loaded with the auth/visibility constraint before purpose and outputs. No filler, though the final sentence is dense with backticked identifiers and chaining instructions packed into one line.

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 non-idempotent, state-creating tool with an output schema, the description covers the essentials an agent needs: no auth, the session it creates, both returned values, and which sibling consumes each. Return-value explanation is a bonus since an output schema already exists.

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 description coverage is 100% with enums documented for agent_client and framework_hint, so the schema carries parameter meaning. The description only alludes to website_url via 'fetches it' and adds no format or constraint detail beyond the schema, matching the baseline 3.

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 concrete verb set and resource: it fetches a public website, detects CMS/platform hints, and creates an onboarding session. It also names two siblings (register_and_provision, get_onboarding_session) and their roles in the flow, so an agent can place it in the workflow. It stops short of an explicit 'use this instead of X' contrast, which keeps it at 4.

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?

'Public discovery; works without auth' plus the explicit chaining rules (register_and_provision consumes both outputs; get_onboarding_session takes the token before sign-up) tell an agent exactly when this tool fits in the sequence. No exclusions or 'when not to use' guidance are given, so it does not reach 5.

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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