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Glama
gosadu

loophole-tape

Outcome labels for up to 40 pump.fun memecoins ($0.01)

mint_outcome_batch

Batch grade your rug or graduation calls for 1–40 pump.fun mints, returning outcome labels and known:false for unseen mints.

Instructions

$0.01 per call whatever the answers. Use to grade a list of your own rug or graduation calls: the outcome labels of 1 to 40 distinct pump.fun mints in the order asked, with the fields and the fixed public rule of mint_outcome; for one mint mint_outcome ($0.001) costs less. Input: mints (each a mint or a pump.fun/gmgn/solscan/birdeye link). A mint we never saw answers known:false. More than 40, a malformed or a repeated mint is refused before payment. No probabilities, no opinions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mintsYesOne to 40 distinct pump.fun mints, each a mint or a pump.fun/gmgn/solscan/birdeye link, known to our capture or not.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing pricing ($0.01 per call regardless of answers), the pre-payment refusal rules (over 40, malformed, or repeated mints), the known:false behavior for unseen mints, order preservation, and the 'no probabilities, no opinions' guarantee. This is exactly the extra context annotations cannot carry.

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?

Front-loads the price and the core action, and every sentence carries information. Slightly dense and clause-heavy in the middle, but no filler or repetition.

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?

No output schema exists, and the description points to 'the fields and the fixed public rule of mint_outcome' rather than enumerating the returned fields, which forces a cross-reference. Everything else an agent needs to call it correctly is present.

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 already 100%, so baseline is 3; the description adds genuine meaning on top — accepted input forms (mint or pump.fun/gmgn/solscan/birdeye link), distinctness, ordering of returned labels, and rejection semantics. It stops short of format details, so not a 5.

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?

States a specific verb and resource ('outcome labels of 1 to 40 distinct pump.fun mints in the order asked') and explicitly distinguishes itself from the sibling mint_outcome by count and price. An agent can route between the batch and single-mint tools without opening either schema.

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?

Gives a concrete use case ('grade a list of your own rug or graduation calls') and names the alternative with its selecting condition ('for one mint mint_outcome ($0.001) costs less'). The when-to-use-this-vs-that decision is fully specified.

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