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agent-ready-kit

by com.mudko

Recommend MCP Tool Names

recommend_tool_names
Read-onlyIdempotent

Use this when planning what agent capabilities a customer should expose. Returns up to 5 ranked snake_case MCP tool names with descriptions and rationale, derived from the site's content + detected vertical. Tool names follow MCP convention (snake_case, action_object) — book_appointment, request_quote, check_inventory, verify_insurance_acceptance, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesSite URL — we'll scrape and detect vertical.
vertical_idNoOptional pre-known vertical id (skip auto-detect).
business_typeNoWhat the customer says they are (e.g. 'pediatric dentist', 'roofing contractor'). Resolved against the schema.org/GBP taxonomy for the canonical schema_type + the standard action set + per-genre analytics + value band.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
genreNo
statusYes
messageNo
suggestionsNo
vertical_idNo
vertical_labelNo
humanFollowupUrlNoURL a calling agent can show its user for the human-rendered version of this tool's output.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds behavioral context: the tool derives recommendations from site content and detected vertical, follows a naming convention, and returns ranked results. This goes beyond what annotations provide.

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

Conciseness5/5

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

Two sentences, no fluff. The first sentence states the purpose and usage context, the second explains the output and naming convention. Every word is necessary.

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?

Given the tool's simplicity and the existence of an output schema, the description provides sufficient information: usage context, input parameters, output content, and naming convention. No gaps identified.

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 100%, but the description adds meaning by explaining that 'url' is used for scraping and vertical detection, 'vertical_id' is optional to skip auto-detect, and 'business_type' is resolved against a taxonomy. This enriches the schema information.

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 clearly states 'Use this when planning what agent capabilities a customer should expose' and specifies that it returns up to 5 ranked snake_case MCP tool names with descriptions and rationale. This is a specific verb-resource pair and stands out among siblings.

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?

The description explicitly provides a usage context ('when planning what agent capabilities a customer should expose'), which is clear and direct. It lacks explicit exclusion criteria or reference to alternative tools, but the context is sufficiently narrow.

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, with descriptions that prevent confusion. Tools like scan_site and run_site_audit are differentiated by their focus on AI-readiness vs. site quality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, with clear action words like 'scan', 'create', 'get', 'verify'. Even longer names like 'summarize_scan_for_humans' maintain consistency.

Tool Count4/5

22 tools is slightly above the ideal range but justified by the comprehensive scope of the server, covering scanning, analysis, quoting, file delivery, and verification. Some tools like generate_files and get_customer_files could overlap but serve different contexts.

Completeness5/5

The tool surface covers the entire workflow from site scanning to deployment verification, with no obvious dead ends. All necessary operations for making a site agent-ready are present, including edge cases like x402 validation and credential verification.

Resources