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indic_ner

Extract Indian names, places, organizations, and festivals from text using named entity recognition. Supports multiple languages with micropayment pricing.

Instructions

Named entity recognition tuned for Indian names, places, organisations, festivals. Cost: $0.005 USDC. Service: indic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
languageYes

Implementation Reference

  • The "indic_ner" tool is dynamically registered and handled by this function, which fetches the registry and dispatches the request based on the tool name.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      const { name, arguments: args } = request.params;
    
      let registry: Registry;
      try {
        registry = await fetchRegistry();
      } catch (error) {
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({ error: "Failed to fetch tool registry", detail: String(error) }),
            },
          ],
        };
      }
    
      const tool = registry.tools.find((t) => t.name === name);
      if (!tool) {
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                error: `Tool '${name}' not found`,
                available_tools: registry.tools.map((t) => t.name),
              }),
            },
          ],
        };
      }
    
      try {
        const result = await callTool(tool, args as Record<string, unknown>);
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(result, null, 2),
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                error: "Tool call failed",
                tool: name,
                service: tool.service,
                detail: String(error),
              }),
            },
          ],
        };
      }
    });
Behavior2/5

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 mentions 'Cost: $0.005 USDC' which is useful financial context, and 'Service: indic' which hints at a specialized service. However, it doesn't disclose critical behavioral traits like whether this is a read-only operation, rate limits, authentication needs, error handling, or what the output format looks like.

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 concise with three short phrases that each add value: the core function, the cost, and the service identifier. There's no wasted verbiage, though it could be slightly more structured for readability.

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

Completeness2/5

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

Given the complexity of an NER tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks information about parameter usage, output format, error conditions, and behavioral constraints that would be necessary for an agent to use this tool effectively.

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

Parameters2/5

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 for the undocumented parameters. The description adds no information about the 'text' or 'language' parameters beyond what the bare schema provides. It doesn't explain what text format is expected, what languages are supported, or provide any examples of valid inputs.

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 performs 'Named entity recognition' with a specific focus on 'Indian names, places, organisations, festivals', which provides a specific verb+resource combination. However, it doesn't explicitly distinguish this from sibling tools like 'detect_code_switching' or 'indic_sentiment' that might also process Indian text, missing full differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It mentions 'tuned for Indian names, places, organisations, festivals' which implies a context, but doesn't specify when-not-to-use cases or name any of the 30+ sibling tools as alternatives for related tasks.

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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