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Smart-money flow for a pump.fun token (what proven wallets are doing)

smartmoney_flow
Read-onlyIdempotent

For a pump.fun token mint: how many proven wallets (statistically positive past results over the last 30 days, net of estimated fees; creators, launch-block buyers, wash-like and clustered wallets removed) bought or sold it in the last 15 min / 1 h / 24 h, their share of active wallets, net SOL flow, first proven entry time (UTC), whether they are exiting, top proven wallets with an anonymous score band, coverage and confidence. Covers pump.fun bonding-curve (pre-graduation) trades only; never estimated. Informational data only, not financial advice; past wallet performance does not predict results. Free/keyless: headline; full report with any API key, or x402 pay-per-call at $0.01 USDC: GET /v1/x402/smartmoney/{mint}.

Input Schema

NameRequiredDescriptionDefault
mintYesToken mint address (Solana base58, pump.fun).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover read-only/idempotent/non-destructive. The description adds value beyond that: access tiers (free headline vs. full report with any API key vs. x402 at $0.01 USDC via a specific endpoint), data-provenance guarantees ('never estimated'), and a disclaimer that results are informational only. It stops short of stating rate limits or error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The essential subject and time windows are front-loaded, but the single dense sentence with stacked parentheticals (proven-wallet definition, fee treatment, exclusions) is hard to parse, and access/pricing details are trailed at the end.

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 single-parameter read tool with no output schema, the description does the heavy lifting on what the response contains (flow counts, share of active wallets, net SOL flow, first entry time, exit signal, wallet score bands, coverage and confidence). Only the response shape and error cases remain unspecified, which is acceptable here.

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% and there is only one parameter, so the baseline is 3; the description earns a bump because it constrains the mint to pump.fun bonding-curve tokens specifically, which the schema's generic 'Token mint address (Solana base58, pump.fun)' only partially conveys.

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?

Opens with a specific verb+resource framing ('for a pump.fun token mint: how many proven wallets bought or sold it in the last 15 min / 1 h / 24 h') and enumerates the metrics returned. It's clearly distinguishable in substance from siblings like creator_reputation or token_manipulation_score, but never names or contrasts those alternatives explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Scope constraints are stated ('pump.fun bonding-curve (pre-graduation) trades only'), which implicitly tells the agent when this applies. However there is no explicit 'use this instead of X when...' routing against the many sibling scoring tools, so the agent must infer selection.

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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