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buy_tok_TSLAB

Paid. Tesla (bStocks Tokenized Stock) (TSLAB) price: live USD price, 24h change and market-cap rank. $0.05 USDC on Base or Solana. No account, no API key. Failed calls not charged. URL https://southpow.media/v1/price/TSLAB.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "buy_tok_TSLAB"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations supplied, the description carries the full burden and does well: it discloses that the call is paid, the exact price and accepted settlement chains, that no account/API key is required, and that failed calls are not charged — a genuinely useful risk/failure policy. It stops short of stating rate limits, response freshness/caching, or what the agent receives on an unpaid (402) invocation, so it is strong but not complete.

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?

Densely front-loaded: 'Paid.' leads, then what data is returned, then cost, then auth, then failure policy. Every sentence carries information, though the trailing raw endpoint URL is redundant for an agent that never needs to construct the request itself and slightly dilutes the structure.

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 zero-parameter tool with no output schema and no annotations, the description covers the essentials: what fields come back, what it costs, on which chains, and that failures are free. The notable gap is the payment mechanism itself — how the agent is expected to settle the $0.05 (e.g. an x402 challenge) — which matters for actually completing the call.

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 takes zero parameters, so the baseline is 4 and there is no parameter meaning to add. The description correctly adds none and instead spends its words on pricing and payment, which is the right allocation for a no-arg call.

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 — the live USD price, 24h change and market-cap rank for TSLAB — and names the issuer ('bStocks Tokenized Stock'), which is what separates it from the many sibling TSLA-tracking tokens (buy_tok_TSLAON, buy_tok_TSLAX, buy_tok_SPY etc.). An agent can tell exactly which asset's price it will receive without opening anything else.

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?

The description implies usage (you buy this call to get TSLAB pricing) and gives strong commercial context — 'Paid', '$0.05 USDC on Base or Solana', 'No account, no API key' — but never says explicitly when to choose this over siblings such as buy_crypto_price, buy_tok_TSLAX or buy_tok_TSLAON, nor any exclusions. The when-to-use is left to be inferred from the asset name.

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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