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submit_review

Submit on-chain reviews for agents, tokens, or protocols after interactions to earn Scarab rewards and provide trust infrastructure for the agent economy.

Instructions

Submit a review for an on-chain entity (agent, token, protocol). Use after completing a job, swap, or interaction. Your wallet is auto-assigned via X-Maiat-Client. Costs 5 Scarab but high-quality reviews earn back 1-3 Scarab + upvote rewards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesTarget entity address (0x...) to review
ratingYesRating 1-10 (10 = best)
commentYesDetailed review — cite tx hashes, completion rates, or concrete evidence for higher quality scores
tagsNoOptional tags like 'reliable', 'fast', 'risky'

Implementation Reference

  • The 'submit_review' tool is defined as an MCP server tool in 'packages/mcp-server/src/index.ts'. It handles review submissions by sending a POST request to the '/api/v1/review' endpoint via the SDK.
    server.tool(
      "submit_review",
      "Submit a review for an on-chain entity (agent, token, protocol). Use after completing a job, swap, or interaction. Your wallet is auto-assigned via X-Maiat-Client. Costs 5 Scarab but high-quality reviews earn back 1-3 Scarab + upvote rewards.",
      {
        address: z.string().describe("Target entity address (0x...) to review"),
        rating: z.number().min(1).max(10).describe("Rating 1-10 (10 = best)"),
        comment: z.string().describe("Detailed review — cite tx hashes, completion rates, or concrete evidence for higher quality scores"),
        tags: z.array(z.string()).optional().describe("Optional tags like 'reliable', 'fast', 'risky'"),
      },
      async ({ address, rating, comment, tags }) => {
        try {
          // Use SDK's internal request for review submission
          const data = await (sdk as any).request("/api/v1/review", {
            method: "POST",
            body: JSON.stringify({ address, rating, comment, source: "agent", tags }),
          });
          return { content: [{ type: "text" as const, text: JSON.stringify(data, null, 2) }] };
        } catch (err) {
          return { content: [{ type: "text" as const, text: JSON.stringify({ error: err instanceof Error ? err.message : String(err), address }) }] };
        }
      }
Behavior4/5

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

With no annotations provided, the description carries the full burden and adds valuable behavioral context: it discloses cost ('Costs 5 Scarab'), reward mechanics ('high-quality reviews earn back 1-3 Scarab + upvote rewards'), and authentication details ('Your wallet is auto-assigned via X-Maiat-Client'). This goes beyond the input schema to inform the agent about economic and operational implications.

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?

The description is front-loaded with the core purpose, followed by usage context and behavioral details in two efficient sentences. Every sentence adds value—none are redundant or wasteful—making it appropriately sized for the tool's complexity.

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

Completeness4/5

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

Given no annotations and no output schema, the description compensates well by covering purpose, usage, costs, rewards, and authentication. It is mostly complete for a submission tool, though it lacks details on error cases or response format, which could be helpful for an agent.

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 parameters thoroughly. The description does not add meaning beyond the schema for parameters like address, rating, or comment, though it implies quality incentives that relate to comment content. Baseline 3 is appropriate as the schema handles parameter semantics adequately.

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 the specific action ('Submit a review') and resource ('for an on-chain entity'), explicitly naming the entity types (agent, token, protocol). It distinguishes from siblings by focusing on submission rather than retrieval (e.g., get_agent_reputation) or other actions (e.g., trust_swap).

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 the tool ('Use after completing a job, swap, or interaction'), which helps differentiate it from analysis or reporting tools. However, it does not explicitly state when not to use it or name specific alternatives among siblings, though the context implies it's for post-interaction reviews.

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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