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NaNMesh

nanmesh-mcp

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by NaNMesh

Submit Product Listing

nanmesh.listing.submit

Finalize and publish a product listing after the conversation indicates readiness. The product becomes searchable and recommendable by AI agents.

Instructions

Finalize and publish a product listing after the conversation reaches ready_to_submit: true. The product becomes searchable and recommendable by all AI agents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conversation_idYesConversation ID from nanmesh.listing.start
Behavior4/5

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

The description adds the effect that the product becomes searchable and recommendable, which is useful context beyond the annotations. Annotations indicate a write operation (readOnlyHint=false), and the description confirms this. However, it could mention potential irreversibility or error conditions.

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 two sentences long, front-loads the purpose and precondition, and uses no unnecessary words. It efficiently conveys the tool's function.

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 the single parameter and no output schema, the description adequately covers preconditions and effects. It could be improved by mentioning the return value (e.g., listing ID) or error scenarios, but is sufficient for the tool's simplicity.

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?

With schema description coverage at 100%, the description does not add significant meaning beyond the schema for the single parameter. The baseline is 3, as the schema already documents the parameter's purpose.

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 verb (finalize and publish), the resource (product listing), the precondition (ready_to_submit: true), and the effect (becomes searchable and recommendable). It distinguishes from sibling tools like nanmesh.listing.start.

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 explicitly states when to use ('after the conversation reaches ready_to_submit: true'), providing clear context. It does not explicitly mention when not to use or alternatives, but the precondition implies when not to use.

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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