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smile-io

Redeem a customer's points for a reward

smile_purchase_points_product
Destructive

WRITE — SPENDS THE CUSTOMER'S POINTS: redeem points on the customer's behalf by purchasing a points product; Smile deducts the points and issues the reward (the response's points_purchase.reward_fulfillment usually holds a discount code). Only do this when the customer asked for it. For a 'variable' product pass points_to_spend; leave it out for 'fixed' products. There is no API to cancel a redemption — a mistaken one can only be compensated with smile_create_points_transaction. Requires the points_purchase:write scope. Smile: POST /points_products/{id}/purchase.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idYesSmile customer ID.
points_to_spendNoPoints to spend — variable-price products only.
points_product_idYesSmile points product ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already flag destructiveHint=true, and the description goes well beyond that: it discloses that points are spent/deducted, that the reward is issued via the response's points_purchase.reward_fulfillment, that there is no cancellation API, and that the points_purchase:write scope is required. This is exactly the additional context the annotation does not carry.

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?

Front-loads the critical WRITE/SPENDS warning, then layers conditions, failure semantics, and scope in compact clauses. No sentence is filler; the density is warranted by the tool's risk profile.

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

Completeness5/5

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

For a destructive write tool with no output schema, the description covers safety (irreversible), auth (scope), branching logic, and even a hint at the response shape (discount code in reward_fulfillment). Nothing an agent needs to invoke it safely is missing.

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 description coverage is 100%, so the baseline is 3. The description adds real conditional meaning: points_to_spend is required only for 'variable' products and must be omitted for 'fixed' products, which the schema's flat per-parameter text does not convey. Customer and product ID semantics are left to the schema.

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?

States a precise verb and resource — redeem points by purchasing a points product — and immediately distinguishes its effect ('Smile deducts the points and issues the reward'). An agent can tell it apart from read-side siblings like smile_get_points_product or smile_list_points_transactions without opening a schema.

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

Usage Guidelines5/5

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

Explicitly states when to use it ('Only do this when the customer asked for it'), how to branch on product type ('pass points_to_spend for variable, leave it out for fixed'), and names the alternative path when something goes wrong ('can only be compensated with smile_create_points_transaction'). All the decision conditions are spelled out.

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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