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register_loyalty_program

Register a deployed token as a loyalty program in the database. B20 tokens are registered as active; legacy ERC-20 as inactive (activate next).

Input Schema

NameRequiredDescriptionDefault
nameYesProgram name
symbolYesToken symbol
cashback_rateNoDefault cashback percent for earn (1–100). Omit for DB default (5).
token_addressYesDeployed token contract address (0x...)
token_standardNo'b20' (default) or 'erc20' (legacy)
expiration_daysNoDuration in days (default: 365)
points_per_dollarNoLoyalty points per $1 spent (1–1000). Omit for DB default (1).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations only state readOnlyHint=false and destructiveHint=false, so the description usefully adds the real side effect: B20 tokens land in 'active' while legacy ERC-20 land 'inactive' pending activation. It does not cover prerequisites such as ownership of the token or duplicate-registration behavior, but the status-outcome disclosure is genuine value beyond the annotations.

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?

Two dense sentences with no filler: the action is stated first, the conditional status behavior second. Nothing could be removed without losing information.

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?

For a 7-parameter mutation with no output schema, the description covers the core action and the status outcome, but omits error/duplicate handling and required authorization over the token address. Adequate for a well-documented schema but incomplete for an agent that needs to know failure modes.

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 baseline is 3; every parameter including defaults for cashback_rate, points_per_dollar, expiration_days and token_standard is already documented in the schema. The description contributes only the conditional consequence of token_standard ('b20' active vs 'erc20' inactive), adding marginal meaning beyond that baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource ('Register a deployed token as a loyalty program in the database') and the second sentence clarifies the active/inactive outcome by token standard. It never names create_loyalty_program or activate_loyalty_program, so an agent must infer the boundary between 'register an existing deployed token' and 'create a program'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by 'deployed token' (use this when a contract already exists) and 'activate next' hints that activate_loyalty_program is the follow-up step for legacy ERC-20s. No explicit when-to-use/when-not guidance or named alternatives are given, leaving selection against create_loyalty_program to inference.

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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