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Update Storefront

neuron_update_storefront

Create or update the seller storefront (nestuge-style page). Handle is auto-generated from the display name if omitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bioNoShort store bio
handleNoURL handle (a-z, 0-9, hyphens). Becomes /s/<handle>.
enabledNoWhether the storefront is public
socialsNoMap of social links e.g. { instagram: 'https://...' }
avatarUrlNo
brandColorNoHex brand colour e.g. #188A56
displayNameNoStore display name

TDQS

A4.3/5.0
Behavior4/5

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

The description discloses important behavior beyond the annotations: the operation is an upsert ('create or update') and that the handle is auto-generated from the display name when omitted. It does not mention whether omitted fields are preserved or reset, but the provided behavioral details are meaningful.

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 concise sentences with no filler. The primary action is front-loaded, and the most important optional behavior is stated succinctly.

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?

The description is adequate for identifying the tool and key behavior, but it leaves gaps: it does not state what happens to omitted fields during an update, and with no output schema it does not indicate what the tool returns. For a 7-parameter upsert tool, a bit more operational detail would improve completeness.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is high at 86%, so the schema already documents most parameters. The description adds extra semantic value by explaining handle auto-generation behavior, which is not fully captured in the schema description.

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 identifies the action as creating or updating a seller storefront, which is more informative than the title alone. It also distinguishes this tool from the many sibling update_* tools by naming the specific resource and its 'nestuge-style page' nature.

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 gives clear context: this tool is for creating or updating a seller storefront. It does not explicitly name alternatives like get_storefront or state when not to use it, but the action and resource are clear enough that an agent can infer the intended 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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TDQS

B3.4/5.0
Disambiguation3/5

Most tools are clearly separated by resource type, but there is meaningful overlap in messaging entry points (send_message, send_whatsapp, compose_message, bot_api_send) and contact ingestion/sync tools (import_contacts, populate_contacts, sync_whatsapp_contacts). The descriptions help disambiguate, but with 309 tools an agent will frequently need to read closely to pick the right one.

Naming Consistency4/5

The overwhelming majority of tools follow a consistent verb_noun snake_case pattern: create_*, get_*, list_*, update_*, delete_*. Minor deviations like sales_stats, lead_stats, wallet_balance, and whoami break the pattern slightly, but overall naming is highly predictable.

Tool Count1/5

309 tools is an extreme count for any MCP server, even a broad platform. This creates significant cognitive load and navigation overhead for agents, and far exceeds the well-scoped 3-15 tool range where coherence is strongest.

Completeness4/5

The tool surface is remarkably comprehensive across bots, contacts, campaigns, flows, knowledge bases, personas, marketplace, wallet, and products. Minor gaps exist — lead sources lack update/delete tools, and there is no single get_task or get_webhook alongside their list/update/delete counterparts — but these are workable gaps rather than dead ends.

Resources