Skip to main content
Glama
andreasd083

amazing-marvin-complete-mcp

unclaim_reward_points

Idempotent

Reverse a reward-point award tied to a task, such as after a misclick or un-completing the task. Only works for task-linked awards; for manual awards, use spend_reward_points instead.

Instructions

Undo a reward-point award tied to a task. Undo a point award (e.g. after a misclick, or when the task was un-completed with unmark_done). Only works for awards tied to a real task ID: Marvin's server stores no entry for MANUAL awards (verified live 2026-08-19, /unclaimRewardPoints responds 404 'No such entry'). Compensate a MANUAL award with spend_reward_points for the same amount instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate YYYY-MM-DD; omit for today (server timezone)
item_idYesTask ID whose award should be undone (determines the point amount). 'MANUAL' is NOT supported — see description.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.0

TDQS

A4.8/5.0
Behavior5/5

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

Beyond annotations, the description discloses that only real task IDs work, that manual awards have no server entry, that the endpoint responds 404 for manual awards, and that spend_reward_points is the correct compensation path. This adds valuable behavioral context not present in the structured annotations.

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 front-loaded with the core purpose and then provides use cases, limitations, and an alternative. There is slight redundancy between the opening sentence and the second sentence ('Undo a reward-point award' vs 'Undo a point award'), but the structure is otherwise tight and scannable.

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?

The tool description covers purpose, trigger scenarios, constraints, error behavior, and alternative handling for manual awards. Since an output schema exists, not detailing return values is acceptable. The description is complete for correct invocation and handling of edge cases.

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 coverage is 100%, so the baseline is 3. The description adds meaning to item_id by clarifying it is a task ID that determines the point amount and that MANUAL is not supported. This goes beyond the schema's basic description, so a 4 is warranted.

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 opens with a specific verb and resource: 'Undo a reward-point award tied to a task.' It clearly distinguishes itself from sibling tools like claim_reward_points and spend_reward_points by focusing on undoing awards and explicitly calling out the unsupported MANUAL case.

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?

The description gives concrete when-to-use scenarios ('after a misclick', 'when the task was un-completed with unmark_done') and an explicit when-not-to-use case (MANUAL awards) with the exact alternative (spend_reward_points for the same amount). This is exemplary routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.