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bmorphism

Manifold Markets MCP Server

award_bounty

Award a bounty to a comment on a Manifold prediction market using market ID, comment ID, and amount.

Instructions

Award bounty to a comment

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contractIdYesMarket ID
commentIdYesComment ID to award bounty to
amountYesAmount of bounty to award

Implementation Reference

  • Zod schema for award_bounty input validation: contractId, commentId, amount
    const AwardBountySchema = z.object({
      contractId: z.string(),
      commentId: z.string(),
      amount: z.number().positive().finite(),
    });
  • src/index.ts:373-385 (registration)
    Registration of the 'award_bounty' tool with name, description, and JSON Schema input definition
    {
      name: 'award_bounty',
      description: 'Award bounty to a comment',
      inputSchema: {
        type: 'object',
        properties: {
          contractId: { type: 'string', description: 'Market ID' },
          commentId: { type: 'string', description: 'Comment ID to award bounty to' },
          amount: { type: 'number', description: 'Amount of bounty to award' }
        },
        required: ['contractId', 'commentId', 'amount']
      }
    },
  • Handler that parses input via AwardBountySchema, then POSTs to /v0/market/{contractId}/award-bounty with commentId and amount
    case 'award_bounty': {
      const params = AwardBountySchema.parse(args);
      const apiKey = process.env.MANIFOLD_API_KEY;
      if (!apiKey) {
        throw new McpError(
          ErrorCode.InternalError,
          'MANIFOLD_API_KEY environment variable is required'
        );
      }
    
      const response = await fetch(`${API_BASE}/v0/market/${params.contractId}/award-bounty`, {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json',
          Authorization: `Key ${apiKey}`,
        },
        body: JSON.stringify({
          commentId: params.commentId,
          amount: params.amount,
        }),
      });
    
      if (!response.ok) {
        throw new McpError(
          ErrorCode.InternalError,
          `Manifold API error: ${response.statusText}`
        );
      }
    
      return {
        content: [
          {
            type: 'text',
            text: 'Bounty awarded successfully',
          },
        ],
      };
    }
Behavior1/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. However, it only states 'Award bounty to a comment' without mentioning whether the action is destructive, requires specific permissions, or has side effects (e.g., deducting mana, changing market state). No behavioral details are disclosed.

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 a single, concise sentence with no wasted words. However, it could be slightly more informative without sacrificing conciseness, e.g., by mentioning the effect on the bounty or the comment. It remains efficient and front-loaded.

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 low complexity (3 required parameters, no output schema, no annotations), the description provides the basic purpose and the schema covers parameter semantics. However, the lack of behavioral context (e.g., whether the action is reversible, permissions needed) makes it less complete than ideal.

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?

The input schema has 100% coverage with clear descriptions for all three parameters (contractId, commentId, amount). The description adds no additional meaning beyond what the schema provides, so the baseline score of 3 applies.

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 'Award bounty to a comment' uses a specific verb and resource, clearly indicating the action. It distinguishes from siblings like 'add_bounty' which likely adds a bounty offer, and other tools like 'place_bet', 'close_market', etc. The purpose is immediately clear.

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?

No guidance is provided on when to use this tool versus alternatives, such as when to use 'add_bounty' instead. The description gives no context about prerequisites, timing, or exclusions, leaving the agent to infer usage solely from the tool name and schema.

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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