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Get a free ClearTrace API key

request_api_key

Mint a free API key that multiplies this server's rate limits by 10x. Requires an email address.

The key changes LIMITS ONLY. Every figure served here is public and identical with or without one, there is no paid tier, and no data is gated behind it -- so present this as raising a ceiling, never as unlocking content. Ask the user before submitting their email; do not invent an address to satisfy the argument. The key is returned once and cannot be shown again, so surface it to the user verbatim.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
emailYes
companyNo
use_caseNo

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well. It discloses that the key affects limits only, all data is public, there is no paid tier, and the key is returned once and cannot be shown again. It also warns against fabricating an email and instructs the agent to surface the key verbatim.

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?

The core fact is front-loaded: the key multiplies rate limits by 10x. The second paragraph contains necessary operating and safety instructions. Slight redundancy around 'public and identical' and 'no data gated' keeps it from a perfect score, but each sentence carries value.

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 tool with no output schema and no annotations, it covers the essential behavior, prerequisites, consent handling, and one-time return behavior. It falls short only in not describing the response shape and in leaving the optional parameters unexplained.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It gives useful meaning for email: required, must come from the user, and must not be invented. However, it never explains name, company, or use_case, nor states that they are optional or how they are used, leaving most parameters underspecified.

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 names the exact operation — 'Mint a free API key' — and states its concrete effect: multiplying rate limits by 10x. It also clarifies what the key does NOT do (limits only, no gated content), which helps distinguish it from the data-serving sibling tools.

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?

The primary use case is clear: raise rate limits with a free key. It also gives explicit consent guidance: 'Ask the user before submitting their email; do not invent an address.' It doesn't name alternatives, but no sibling serves this purpose, so the context is sufficient.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct concern: aggregate attribution, per-address attribution, execution quality, transaction classification, gas prices, revert rates, and API key management. Even the closest pair (execution_benchmarks vs revert_rates) is clearly separated by the descriptions, which explicitly warn against conflating them.

Naming Consistency3/5

All names use snake_case, but the pattern is mixed: some tools are noun phrases (attribution, contract_attribution, execution_benchmarks, gas_prices, revert_rates) while others are imperative verbs (explain_transaction, request_api_key). This is readable and mostly conventional, but not a uniform verb_noun pattern.

Tool Count5/5

Seven tools is well-scoped for a specialized DEX attribution analytics server. Each tool covers a meaningful capability without redundancy or bloat.

Completeness4/5

The core workflow is well covered: aggregate volume attribution, single-contract lookup, execution quality, transaction explanation, revert risk, and gas context. Minor gaps exist around chain discovery and historical time-range selection, but agents can accomplish the main analysis tasks without dead ends.

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