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get_wheel_of_innovation

Analyze patent data to visualize technology trends and keyword associations using a two-tiered hierarchical view based on recent publications.

Instructions

Provides a two-tiered hierarchical view of keywords/phrases in a technology space. Identify common terms and their associations. Based on the most recent 5,000 publications. Either keywords or IPC classification must be specified.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsNoKeywords to search within patent title and abstract/summary. Supports AND, OR, NOT logic. Example: "mobile phone AND (screen OR battery)"
ipcNoPatent IPC classification code. Used to specify a particular technology field.
apply_start_timeNoPatent application start year (yyyy format). Filters by application filing date.
apply_end_timeNoPatent application end year (yyyy format). Filters by application filing date.
public_start_timeNoPatent publication start year (yyyy format). Filters by publication date.
public_end_timeNoPatent publication end year (yyyy format). Filters by publication date.
authorityNoPatent authority code (e.g., CN, US, EP, JP). Filters by patent office. Use OR for multiple, e.g., "US OR EP".
langNoLanguage setting. Default is "en" (English). Choose "cn" (Chinese) or "en".

Implementation Reference

  • The core handler function for the 'get_wheel_of_innovation' tool. It constructs URLSearchParams from input arguments, sets a default language if not provided, and delegates to the shared callPatsnapApi helper function targeting the 'wheel-of-innovation' endpoint.
    async function getWheelOfInnovation(args: LangPatentArgs): Promise<ServerResult> {
      const params = buildCommonSearchParams(args);
      if (!args.lang) { // Add default lang if not provided
          params.append('lang', 'en');
      }
      return callPatsnapApi('wheel-of-innovation', params, 'get wheel of innovation');
    }
  • Input schema definitions used by the tool: basePatentInputSchema for common patent search parameters, and langPatentInputSchema extending it with optional 'lang' field.
    const basePatentInputSchema = {
        type: 'object' as const, // Use 'as const' for stricter type checking
        properties: {
            keywords: { type: 'string', description: 'Keywords to search within patent title and abstract/summary. Supports AND, OR, NOT logic. Example: "mobile phone AND (screen OR battery)"' },
            ipc: { type: 'string', description: 'Patent IPC classification code. Used to specify a particular technology field.' },
            apply_start_time: { type: 'string', description: 'Patent application start year (yyyy format). Filters by application filing date.' },
            apply_end_time: { type: 'string', description: 'Patent application end year (yyyy format). Filters by application filing date.' },
            public_start_time: { type: 'string', description: 'Patent publication start year (yyyy format). Filters by publication date.' },
            public_end_time: { type: 'string', description: 'Patent publication end year (yyyy format). Filters by publication date.' },
            authority: { type: 'string', description: 'Patent authority code (e.g., CN, US, EP, JP). Filters by patent office. Use OR for multiple, e.g., "US OR EP".' }
        },
        // Add a note about requiring keywords or IPC for most tools
        description: "Requires either 'keywords' or 'ipc' to be specified for a meaningful search. If both are provided, IPC is prioritized by the API."
    };
    
    const langPatentInputSchema = {
        ...basePatentInputSchema,
        properties: {
            ...basePatentInputSchema.properties,
            lang: { type: 'string', description: 'Language setting. Default is "en" (English). Choose "cn" (Chinese) or "en".' }
        }
    };
  • TypeScript type definitions for the tool's input arguments, matching the JSON schemas.
    type BasePatentArgs = { keywords?: string; ipc?: string; apply_start_time?: string; apply_end_time?: string; public_start_time?: string; public_end_time?: string; authority?: string };
    type LangPatentArgs = BasePatentArgs & { lang?: string };
  • src/index.ts:346-350 (registration)
    Registration of the tool in the ListToolsRequestSchema handler, specifying name, description, and input schema.
    {
      name: 'get_wheel_of_innovation',
      description: 'Provides a two-tiered hierarchical view of keywords/phrases in a technology space. Identify common terms and their associations. Based on the most recent 5,000 publications. Either keywords or IPC classification must be specified.',
      inputSchema: langPatentInputSchema
    },
  • src/index.ts:393-404 (registration)
    Dispatch map registering the tool name to its handler function for use in the CallToolRequestSchema handler.
    const toolImplementations: Record<string, (args: any) => Promise<ServerResult>> = {
        'get_patent_trends': getPatentTrends,
        'get_word_cloud': getWordCloud,
        'get_wheel_of_innovation': getWheelOfInnovation,
        'get_top_authorities_of_origin': getTopAuthoritiesOfOrigin,
        'get_most_cited_patents': getMostCitedPatents,
        'get_top_inventors': getTopInventors,
        'get_top_assignees': getTopAssignees,
        'get_simple_legal_status': getSimpleLegalStatus,
        'get_most_litigated_patents': getMostLitigatedPatents,
        'get_portfolio_value_distribution': getPortfolioValueDistribution, // Add new tool here
    };
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about the data source ('most recent 5,000 publications') and the requirement for keywords or IPC. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, potential rate limits, authentication needs, error conditions, or what the hierarchical view output looks like. For a tool with 8 parameters and no output schema, this leaves significant gaps.

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?

The description is appropriately sized with three sentences that each earn their place: first states the purpose, second adds data source context, third provides critical usage constraint. It's front-loaded with the core functionality. There's no wasted text, though it could be slightly more structured for clarity.

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

Completeness3/5

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

Given the tool's complexity (8 parameters, no output schema, no annotations), the description is moderately complete. It covers purpose, data scope, and a key constraint, but lacks details about output format, behavioral characteristics, and differentiation from siblings. Without annotations or output schema, the agent would need to infer or test these aspects, making this description adequate but with clear gaps for effective tool selection and invocation.

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%, so the schema already documents all 8 parameters thoroughly with examples and logic. The description adds minimal value beyond the schema: it emphasizes that 'either keywords or IPC classification must be specified' and mentions IPC prioritization when both are provided. This provides some semantic clarification but doesn't add significant meaning beyond what's in the well-documented schema.

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?

The description clearly states the tool 'provides a two-tiered hierarchical view of keywords/phrases in a technology space' and 'identifies common terms and their associations', which specifies the verb (provides/identifies) and resource (keywords/phrases in technology space). It distinguishes from siblings by focusing on hierarchical keyword analysis rather than citation counts, litigation, trends, or other patent metrics. However, it doesn't explicitly contrast with 'get_word_cloud' which might be a closer sibling.

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 provides clear context for when to use this tool: 'Based on the most recent 5,000 publications' and 'Either keywords or IPC classification must be specified.' This gives practical constraints and prerequisites. However, it doesn't explicitly state when NOT to use it or name alternatives among the sibling tools (e.g., when to choose this over 'get_word_cloud' or 'get_patent_trends').

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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