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skylight_create_reward

Create a redeemable family reward in Skylight Calendar by setting its name, point value, categories, and whether it respawns after redemption.

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.

  1. Changed1 schema field changedv1.0.1
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. 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"
      +]
  3. First observedv0.4.6

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already establish this is a non-read-only, open-world, non-destructive write, so the safety profile is covered. The phrase 'live-verified fields' is a genuine value-add, implying other schema fields (e.g. frameId) are unverified, but the description says nothing about required pre-existing categories, failure modes, or what is returned.

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?

A single tight sentence with no filler, and the verb+resource leads. The parenthetical field list is compact rather than padded.

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 create tool with no output schema and no annotations gap, the description is minimally adequate but omits the cross-entity dependency (category_ids must reference existing category ids) and any note on the unverified frameId behavior.

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 coverage is 67% and the description names five of the six parameters, but it only repeats names already present in the schema and skips frameId entirely. No added meaning on format or constraints beyond what the schema already states.

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?

Clear specific verb+resource ('Create a reward') and it enumerates the fields the tool accepts, so an agent knows exactly what it produces. It does not, however, differentiate itself from near neighbors like skylight_create_category or the reward-update tool beyond the obvious verb.

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?

No statement of when to use this versus skylight_update_reward or how it relates to skylight_create_category for the referenced category_ids. An agent must infer context entirely from the name and schema.

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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