Solana Pulse: agent safety layer

token_traders

Read-onlyIdempotent

Run to see who bought a token early and who profited: launch-block snipers, the pool creator, wallets that sold more than they bought (got tokens some other way), and ordinary traders. Reads a token's pool from its first transaction for a set time and lists the wallets that traded it: buys, sells, SOL spent and received, profit, how soon after launch they bought, and launch-block and creator flags. Example: {"token": "", "hours": 6}. Cost: 25 free calls a day, then $0.03 USDC per call (x402). Outputs explained: GET /api/tools/token_traders.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "token": "<token>"
    },
    "name": "token_traders"
  }
}

Input Schema

Name	Required	Description	Default
`pool`	No	The pool to read. Default: the pool with the most liquidity in RugCheck's report. A DEX page or GeckoTerminal's pool address.
`hours`	No	How long after the pool's first transaction to read (default 6). Short (1-2) to study the launch, longer to see who held.
`token`	Yes	The token whose traders you want. find_token, or the token's address from the user. Never make one up.
`network`	No	Default "mainnet-beta" (real money). "devnet" only for test wallets.	mainnet-beta
`how_many`	No	How many wallets to list, most profit first (default 25). Default is fine.
`max_trades`	No	At most this many transactions are read, oldest first (default 400). Raise it for busy pools; the answer says when the window was cut short.

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), and the description adds genuinely new behavioral facts: rate limits and pricing (25 free calls/day, then $0.03 USDC via x402), that the read window starts at the pool's first transaction, and that max_trades can truncate the window with the response flagging it. These are the kind of operational details annotations cannot express.

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?

Purpose and target archetypes are front-loaded, followed by what is read and returned, then a concrete example, cost, and a docs pointer. It is a dense single paragraph that borders on run-on, but every sentence carries information an agent would otherwise have to guess.

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?

There is no output schema, and the description compensates by enumerating the returned fields (buys, sells, SOL spent/received, profit, time-after-launch, launch-block and creator flags) plus a docs URL. Combined with pricing and the truncation caveat, an agent has everything needed to call and interpret this 6-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents pool, hours, token, network, how_many and max_trades thoroughly. The description only reinforces token and hours via the example call and the "reads from first transaction" framing, adding little beyond the structured fields; baseline 3 is appropriate.

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 outcome ("see who bought a token early and who profited") and then enumerates the wallet archetypes returned: launch-block snipers, pool creator, wallets that sold more than they bought, ordinary traders. That is far more specific than the tool name alone and clearly separates it from siblings like find_token (address lookup) and token_safety (risk checks).

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

Usage Guidelines4/5

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

It gives a clear context for use (early-buyer/profit analysis of a token) and points to find_token for obtaining the mint, and the example call shows the typical invocation. It stops short of explicit when-not guidance or naming an alternative tool (e.g. history or trace) for adjacent questions, so a 4 rather than a 5.

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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