Skip to main content
Glama

t2000_pending_rewards

Check pending protocol rewards from lending positions without claiming them. Shows claimable reward tokens per protocol and asset.

Instructions

Check pending protocol rewards from lending positions WITHOUT claiming them. Shows claimable reward tokens per protocol and asset. Use t2000_claim_rewards to actually collect and convert to USDC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler for the 't2000_pending_rewards' tool, which calls 'agent.getPendingRewards()'.
    server.tool(
      't2000_pending_rewards',
      'Check pending protocol rewards from lending positions WITHOUT claiming them. Shows claimable reward tokens per protocol and asset. Use t2000_claim_rewards to actually collect and convert to USDC.',
      {},
      async () => {
        try {
          const result = await agent.getPendingRewards();
          return { content: [{ type: 'text', text: JSON.stringify({ rewards: result, count: result.length }) }] };
        } catch (err) {
          return errorResult(err);
        }
      },
Behavior4/5

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

With no annotations provided, the description carries the full burden. It effectively discloses key behavioral traits: it's a read-only operation (doesn't claim rewards), shows claimable tokens per protocol and asset, and implies it returns informational data. However, it doesn't mention potential limitations like rate limits or authentication requirements.

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?

Two sentences with zero waste: the first states purpose and key constraint, the second provides explicit alternative. Every word earns its place, and the most critical information is front-loaded.

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

Completeness4/5

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

For a parameterless tool with no annotations and no output schema, the description is quite complete: it explains what the tool does, what it doesn't do, and provides an alternative. However, without an output schema, it could benefit from mentioning the format of returned data (e.g., structured list of protocols/assets).

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?

The tool has 0 parameters with 100% schema coverage, so the baseline is 4. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose and behavior, which is correct for a parameterless tool.

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 clearly states the specific action ('Check pending protocol rewards') and resource ('from lending positions'), explicitly distinguishing it from the sibling tool t2000_claim_rewards by emphasizing 'WITHOUT claiming them'. This provides precise differentiation.

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?

It explicitly states when to use this tool ('Check pending protocol rewards... WITHOUT claiming them') and when to use an alternative ('Use t2000_claim_rewards to actually collect and convert to USDC'), providing clear guidance on tool selection.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mission69b/t2000'

If you have feedback or need assistance with the MCP directory API, please join our Discord server