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SolVerdict

by co.youraitools
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Solana token safety check

check_solana_token
Read-onlyIdempotent

Safety check for any Solana SPL or Token-2022 mint before an agent or app interacts with it. SAFE / CAUTION / DANGER with a 0-100 score, from mint and freeze authority, Token-2022 extensions that can block or tax sells, liquidity and recent sells, holder concentration and age. Free preview tier: verdict, score and flag counts. The paid x402 endpoints /v1/lite ($0.005) and /v1/check ($0.02) add the reasons and evidence. SAFE is not a guarantee and not financial advice.

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": {
      "mint": "<mint>"
    },
    "name": "check_solana_token"
  }
}

Input Schema

NameRequiredDescriptionDefault
mintYesSolana token mint address (base58), e.g. DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263 (BONK)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already cover safety (readOnly, idempotent), and the description adds substantial context beyond them: the output vocabulary (SAFE/CAUTION/DANGER with a 0-100 score), the signals feeding the verdict, what the free tier returns versus the paid x402 endpoints, and an explicit non-guarantee disclaimer. This is exactly the extra behavioral layer the annotations cannot convey.

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?

Front-loads purpose, then verdict scale, then input signals, then tier/pricing detail, then disclaimer. Four dense sentences with no filler, ordered by what an agent needs first.

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, so the description must describe returns — and it does, naming the verdict, score, flag counts, and what the paid tiers add. It is effectively complete for a single-parameter read tool, with only error/invalid-mint behavior left unstated.

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?

With one parameter at 100% schema description coverage (including a worked base58 example), the schema carries the full burden and the description need not compensate. The description does not touch the `mint` argument at all, so 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?

States a specific verb and resource ('Safety check for any Solana SPL or Token-2022 mint') and scopes the timing ('before an agent or app interacts with it'). An agent immediately knows this is a pre-interaction risk assessment on a mint address.

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?

Clearly signals when to use it (before interacting with a token) and explains the free-vs-paid tier split so an agent can decide which endpoint depth it needs. It stops short of explicit when-not-to-use conditions, but there are no siblings to disambiguate against.

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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