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minia2a-mcp

x402-allowance-scan

Allowance Scan: Scan token allowances and approvals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoChain to process
ownerNoOwner to process
tokenNoToken to process
addressNoAddress to process
spenderNoSpender to process

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, but it reveals only the verb 'scan'. It never states what is returned (list of allowances? aggregate amounts?), whether it scans one owner across many tokens, what the address/token/spender filters mean, or even that the operation is a read-only on-chain lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The definition is very short, but this is under-specification rather than disciplined conciseness. The 'Allowance Scan:' prefix redundantly restates the tool name, and the remaining single clause contributes no decision-relevant detail beyond locating the topic.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a 5-parameter tool with no annotations, no output schema, and a confusingly similar sibling (x402-token-allowance). The description fills almost none of those gaps: no return shape, no required parameter combinations, no chain semantics, and no differentiation from adjacent allowance/scan tools.

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% — all five parameters have descriptions — so the baseline of 3 applies even though the tool description itself names no parameters. The schema descriptions are generic placeholders ('Owner to process', 'Address to process', 'Spender to process') that fail to clarify the relationship between owner, address, and spender, but the description adds nothing on top of the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a verb ('Scan') and a resource ('token allowances and approvals'), so it is not a pure tautology. However, 'scan' is a generic verb that doesn't say what the operation produces, the leading 'Allowance Scan:' just restates the tool name, and the description gives no way to distinguish this from the near-identical sibling x402-token-allowance.

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

Usage Guidelines2/5

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

There is zero guidance on when to use this tool versus alternatives. With all 5 parameters optional and a sibling list packed with overlapping blockchain tools (x402-token-allowance, x402-wallet-scan, x402-contract-scan, x402-token-intel), an agent cannot tell what parameter combination forms a valid scan or which tool is the right choice.

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

D1.6/5.0
Disambiguation1/5

The tool set is saturated with near-duplicates and synonyms: character-count vs char-count, clamp vs clamp-value, is-abundant vs is-abundant-num vs is-abundant-number, and fetch vs browser-scrape vs web-scrape vs text-scrape. Generic names like 'difference', 'normalize', 'range', and 'partition' make the boundaries even harder for an agent to determine.

Naming Consistency2/5

Most tools share a x402- kebab-case prefix, but the set mixes noun-only names (math, hash, prime, time), verb-first names (get_stats, find, validate), auto-generated names (x402-publish-1787853294312-base-account), and inconsistent variants like temp vs temperature vs temperature-convert. This is not a coherent verb_noun convention despite the common prefix.

Tool Count1/5

1677 tools is an extreme count that creates selection paralysis and makes coherent agent use impractical. A utility or marketplace server at this scale needs sub-services or namespacing rather than a flat tool list.

Completeness2/5

The surface has broad token coverage across many utility categories, but the marketplace aspect is incomplete: service_discovery and get_stats exist, yet there are no generic publish, update, delete, or account-management operations. Utility families also contain redundant variants without clear completion or lifecycle structure.

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