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rsnc_agent_onboard_brand

Register a new brand on the Resonance cashback network. Creates their account, generates credentials (accessible via partner portal), and sends a welcome email. Requires agent authentication with onboarding permission.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
websiteNoBrand website URL.
categoryNoIndustry category (retail, dining, travel, gaming, other).
descriptionNoShort description of the business.
brandAddressYesBrand's public wallet address (Ethereum format, 0x-prefixed).
businessNameYesBrand/business name.
contactEmailYesContact email — becomes their portal login.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
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 of behavioral disclosure. It explains the side effects: 'Creates their account, generates credentials (accessible via partner portal), and sends a welcome email.' It also states the permission requirement. This is a solid level of transparency, though it could mention what happens if the brand already exists.

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 three concise sentences, each adding distinct value: the core action, notable side effects, and an access requirement. No filler or repetition. It is front-loaded with the action verb and resource.

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?

For a tool with 6 parameters, no output schema, and no annotations, the description covers the essential context: what it does, what gets created, how credentials are accessed, and what permission is needed. It lacks details on return values or failure modes, but for an onboarding tool, this is close to complete.

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 all parameters already have clear descriptions in the schema. The tool description itself does not add further parameter meaning, such as explaining how fields relate or providing format details beyond what the schema states. Baseline 3 is appropriate.

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 begins with a specific verb+resource: 'Register a new brand on the Resonance cashback network.' This clearly distinguishes it from sibling tools, which focus on analytics, perks, or events rather than brand creation.

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 this tool (registering a new brand) and even specifies a prerequisite: 'Requires agent authentication with onboarding permission.' It does not explicitly name alternatives, but no other sibling tool handles brand onboarding, so the usage context is strong.

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

B3.3/5.0
Disambiguation2/5

Several tools have overlapping purposes, e.g., rsnc_agent_best_deals, rsnc_agent_route_purchase, and rsnc_agent_compare_cashback all help find the best purchase/reward option. Similarly, rsnc_agent_network_info, rsnc_agent_network_stats, and rsnc_agent_network_analytics provide similar network overview data with unclear boundaries.

Naming Consistency3/5

All tools share the consistent 'rsnc_agent_' prefix, but the remainder mixes verb-first patterns (browse_perks, claim_reward, create_event) with noun-first patterns (brand_analytics, network_flows, perk_intelligence). This inconsistency makes the tool surface less predictable than a uniform verb_noun scheme.

Tool Count2/5

With 45 tools, the server feels over-scoped for a rewards network. While the domain is broad, many tools are highly granular analytics variations, and the count exceeds the 25+ threshold, adding cognitive load and diminishing coherence.

Completeness4/5

The tool set covers the core lifecycle: brand discovery, onboarding, event/perk creation and updates, reward processing, user balance/stats, and redemption. Minor gaps exist, such as no delete operations for events/perks and no direct user listing, but agents can work around these.

Resources