On-Demand-Books
Server Details
Find personalized puzzle books by first name from a 100,000+ title Shopify catalog.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.4/5 across 3 of 3 tools scored.
Each tool has a distinct purpose: search_books finds books by name, get_book refreshes details for a specific handle, and suggest_names helps with name discovery. There is no overlap.
All tool names follow a consistent verb_noun pattern with underscores: get_book, search_books, suggest_names. No mixing of conventions.
With 3 tools, the set is small but well-scoped for the narrow domain of personalized puzzle books. It covers search, detail retrieval, and name suggestions, though slightly minimal.
The tools cover the key user journey: finding books by name, getting suggestions for names, and retrieving detailed info for a specific book. No obvious gaps for the intended use.
Available Tools
3 toolsget_bookOn-Demand-Books: Get Book by HandleAInspect
Re-resolve a single book's purchase URL, cover image, and ISBN from its Shopify product handle. Use this to refresh or re-reference a book across turns without re-running the full name search.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes | Shopify product handle (as returned in the `shopify_handle` field of a `search_books` result). | |
| utm_source | No | Optional UTM source tag for marketing attribution (e.g. 'mcp.so', 'claude', 'hn'). Appended as ?utm_source=<value> to the Shopify product URL. Defaults to 'mcp'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description implies idempotent read operation but does not explicitly state safety, permissions, or rate limits. Returns three fields but no detail on error cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action and outcome, then usage context. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, description lists three key return fields (URL, image, ISBN). Adequate for the tool's purpose; could mention other possible fields but not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters fully (100%). Description adds default value for utm_source and explains how it's used in URL, providing extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool re-resolves purchase URL, cover image, and ISBN from a Shopify handle. It distinguishes from siblings by mentioning avoiding full name search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use for refreshing or re-referencing a book across turns without rerunning search_books. Implicitly not for initial search or name suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_booksOn-Demand-Books: Search Personalized BooksAInspect
Search for personalized puzzle books by first name. Returns matching books with direct Shopify purchase links, cover images, and ISBNs. A typical exact match returns 9 books across 3 puzzle types (mazes, name-sudokus, word searches) and 3 difficulty levels. When no exact match exists, returns similarly-named books. Use this whenever a user is shopping for a personalized gift and knows the recipient's first name.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | First name to search for personalized puzzle books (e.g. 'Susan', 'Bob'). Case-insensitive; non-letters are stripped. | |
| utm_source | No | Optional UTM source tag for marketing attribution (e.g. 'mcp.so', 'claude', 'hn'). Appended as ?utm_source=<value> to all Shopify product URLs so the seller can track which channel drove the sale. Defaults to 'mcp'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It describes typical result counts for exact matches, behavior for non-exact matches, and what is returned. It lacks explicit mention of read-only nature or rate limits, but is sufficient for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise at 4 sentences, front-loading the main purpose. The extra sentences about typical results and no-match behavior add value without being overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, no output schema), the description fully covers input behavior, return format (links, images, ISBNs, typical count), and usage context. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant detail beyond the schema: case-insensitivity, non-letter stripping for 'name', and UTM source behavior for 'utm_source'. Schema coverage is 100%, so description enriches parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches for personalized puzzle books by first name and specifies the return items (Shopify purchase links, cover images, ISBNs). It also distinguishes from siblings by focusing on name-based search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit usage scenario is given: 'Use this whenever a user is shopping for a personalized gift and knows the recipient's first name.' However, it does not explicitly mention when not to use it or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
suggest_namesOn-Demand-Books: Suggest Available NamesAInspect
Suggest first names for which personalized puzzle books are likely available. Use this when a user is unsure of a spelling, wants gift-recipient ideas, or only has part of a name. Returns popular available names, optionally filtered by a case-insensitive prefix. To confirm a specific name has matching books, follow up with search_books.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of suggestions to return (default 20, max 100). | |
| prefix | No | Optional name prefix to complete (e.g. 'su' -> 'Susan', 'Susie', 'Suzanne'). If omitted, returns a curated list of popular names. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that it returns popular available names with optional case-insensitive prefix filtering. Could mention it's read-only and does not modify data, but overall adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose, second gives usage guidelines and follow-up. Every sentence earns its place with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description doesn't specify return format (e.g., list of strings). Understands context of sibling tools and use case, but could be more complete about the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage describing both parameters. Description adds context like 'popular names' and explains prefix behavior with example, providing value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool suggests first names for available puzzle books, using a specific verb 'suggest' and resource. It distinguishes from siblings by mentioning follow-up with search_books.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use (unsure spelling, gift ideas, partial name) and advises to follow up with search_books for confirmation. Provides clear context and alternatives.
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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