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skylight_create_reward

Create a reward on the Skylight family hub with required name, point value, and category IDs; optionally add a description and enable respawn for repeat redemptions.

Instructions

Create a reward (live-verified fields: name + description + point_value + respawn_on_redemption + category_ids).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesReward name.
frameIdNo
descriptionNo
point_valueYesPoints required to redeem (required).
category_idsYesFamily-member category ids this reward applies to (required).
respawn_on_redemptionNoIf true, the reward can be redeemed repeatedly (respawns after redemption).

Schema Changelog

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

  1. Changed2 schema fields changedv0.7.1
    • removedInput schema / properties / category_ids / items / anyOf
      Removed value: -[
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "number"
      -  }
      -]
    • addedInput schema / properties / category_ids / items / type
      Added value: +[
      +  "string",
      +  "number"
      +]
  2. First observedv0.4.6

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Create a reward' and lists fields; it does not explain side effects, required permissions, validation behavior, idempotency, or what happens on success/failure. The phrase 'live-verified fields' is vague and does not meaningfully disclose behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, action-first sentence with a compact parenthetical field list. It is concise and efficient, though 'live-verified fields' is an unclear phrase that slightly reduces clarity.

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

Completeness2/5

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

For a mutation tool with 6 parameters, no annotations, and no output schema, this description is too thin. It does not explain return values, side effects, prerequisites, or the meaning of frameId, leaving important gaps for an agent deciding how to call the tool correctly.

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 descriptions already cover 4 of 6 parameters, and the description enumerates five field names, which partially helps identify relevant inputs. However, it adds little semantic meaning beyond the schema and does not clarify the purpose of frameId or the 'description' parameter.

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 states a specific verb and resource: 'Create a reward.' It also enumerates the main fields involved, making the tool's purpose unmistakable and distinguishable from update_reward, delete_reward, list_rewards, and get_reward siblings.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus update_reward, or about prerequisites for creating a reward. The imperative 'Create' only restates the tool's name and does not provide context, exclusions, or alternatives.

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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