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minia2a-mcp

x402-api-key-detect

API Key Detect: Detect exposed API keys in text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputNoInput to process

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only scanning operation but never states what happens to the input, what the output looks like (matches, locations, redactions, confidence scores), which API key formats are covered, or whether it makes network calls. For a security-related detection tool, this is a significant transparency gap.

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

Conciseness3/5

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

The description is only two sentences, so it is brief and front-loaded with the purpose. However, the opening 'API Key Detect:' is redundant filler that simply restates the tool name and earns no place. The useful content is confined to the second sentence.

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

Completeness3/5

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

For a single-parameter tool this is minimally viable: an agent can infer that text should be passed and detection results returned. But with no output schema and no annotations, the description should compensate by describing return values, error behavior, or the scope of 'exposed' — none of which are covered. The contract is partially specified but the output side is entirely opaque.

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%, but the parameter description 'Input to process' is a generic placeholder. The tool description adds modest meaning by clarifying that the input is 'text' to be scanned for exposed API keys, which rules out file paths or URLs. This is a minor enhancement over the schema, meeting the baseline for high coverage.

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

Purpose4/5

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

The description states a specific verb and resource: 'Detect exposed API keys in text.' It clearly identifies the tool's function. However, the prefix 'API Key Detect:' merely restates the tool name, and the description does not differentiate it from closely related siblings like x402-secret-scan or x402-password-leak.

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?

No guidance is provided on when to use this tool instead of alternatives. There is no mention of what distinguishes it from x402-secret-scan (which likely also scans for exposed credentials), what text formats are appropriate, or when an agent should choose a different tool. An agent must infer usage entirely from the 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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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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