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token_compare

Read-onlyIdempotent

2-5 candidates in, one ranked pick out — Agents choose between tokens, not around them. Pass 2-5 Base token addresses → each gets a 0-100 quality score (safety-weighted: rug score first, then liquidity depth, then momentum), ranked best-first, with a named pick — or an honest 'none pass the gate'. One call returns a decision instead of a dozen data dumps. Required input: addresses. Priced $0.05 per call over x402 on Base; send a prepaid x-credit-token header for unlimited calls, or get 1 free call/day per tool. No API key required.

Input Schema

NameRequiredDescriptionDefault
addressesYesToken addresses (comma-separated, 2-5)

Output Schema

NameRequiredDescriptionDefault
dataNoThe result payload. Shape is service-specific; every field is documented in the tool description.
serviceNoThe service id that answered.
checkedAtNoISO-8601 timestamp of when the underlying reads were taken.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / properties / data / description
      Previous value: -"The result payload. Shape is service-specific; every field is documented in the service description above."New value: +"The result payload. Shape is service-specific; every field is documented in the tool description."
  2. Changed1 schema field changed
    • removedOutput schema / required
      Removed value: -[
      -  "data"
      -]
  3. Added

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing the scoring methodology and its priority order (rug score, then liquidity, then momentum), the best-first ranking, the 'none pass the gate' outcome, the $0.05 x402 price on Base, the prepaid x-credit-token header, and the 1 free call/day limit. Annotations only cover safety/idempotency, so this behavioral and commercial detail is genuinely additive.

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 core purpose in the first clause and follows with methodology, output, and payment in a logical order. It is slightly padded with a slogan ('Agents choose between tokens, not around them') and a long payment sentence, but nothing is genuinely off-topic.

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?

An output schema exists, so return values need not be spelled out, and the description still covers chain, scoring weights, ranking direction, gate-failure behavior, and payment/auth requirements. An agent has everything needed to call and interpret this 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 coverage is 100% and the single parameter is fully documented ('Token addresses (comma-separated, 2-5)'), so the schema does the heavy lifting. The description adds only the chain specificity ('Base token addresses') and repeats the 2-5 range, which is marginal value; baseline 3 applies.

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 (compare/rank) and resource (2-5 Base token addresses) with the exact output shape: 0-100 scores, best-first ranking, and a named pick. It is clearly distinguishable from single-token siblings like rug_score, token_risk, and token_momentum because it is the only one that takes a candidate set and returns a decision.

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?

Gives clear context for use ('choose between tokens') and implicitly contrasts against the alternative of gathering 'a dozen data dumps' from multiple single-token tools. However, it never names a sibling tool or states an explicit exclusion (e.g., when NOT to use it), so the guidance is clear but not fully prescriptive.

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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