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Glama

land_liquidity_allrewards

List the token, pool ID, and reward total for each of the 12 land liquidity rewards. Returns the raw pairs exactly as provided by the endpoint, showing DEC and each pool's resource token.

Instructions

List the 12 real (token, liquidity_pool_id) reward-total pairs returned by GET /land/liquidity/allrewards. DEC appeared once for each of the six observed pools, and each pool's own resource token appeared once. reward_total and liquidity_pool_id are JSON numbers and token is a string. This tool returns the rows unchanged and does not derive totals or pool membership.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It proactively discloses that the tool 'returns the rows unchanged and does not derive totals or pool membership,' and explains the observed pool/reward pattern. This is valuable beyond the tool's name and schema.

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 well-structured, starting with the primary action and then providing detail. A couple of sentences are somewhat verbose (e.g., the six-pool explanation), but each sentence adds meaningful context without redundancy.

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?

Despite having no output schema and no annotations, the description fully specifies what is returned: exact row count, field types, and behavioral guarantees. For a zero-parameter list tool, this is complete and sufficient for an agent to understand the result.

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?

There are zero parameters, so the baseline is 4. The description does not need to add parameter meaning. It does clarify the data types and row composition, which compensates for the absence of an output schema.

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 clearly states the verb 'List' and the resource: 'the 12 real (token, liquidity_pool_id) reward-total pairs' from GET /land/liquidity/allrewards. It is specific and distinct in content, though it does not explicitly compare against sibling tools.

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 guidance is given about when to use this tool versus alternatives. While the endpoint is unique among siblings, the description does not mention selection criteria, use cases, or exclusions, leaving the agent to infer usage from the name alone.

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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