AGORA Omega

agora_ai_act_check

EU AI Act art. 50 transparency check: is an AI disclosure required, is it present, plus the disclosure text and machine-readable metadata to add. Price: $0.02 USDC per call, paid with x402.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "texte": "<texte>"
    },
    "name": "agora_ai_act_check"
  }
}

Input Schema

Name	Required	Description	Default
`texte`	Yes
`langue`	No
`contexte`	No
`relu_par_humain`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

C2.7/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose the critical behavioral trait of cost and payment mechanism ($0.02 USDC per call via x402) and hints at the response content, but omits auth requirements, rate limits, or what happens with the supplied text.

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?

A compact two-clause sentence that front-loads the regulatory purpose before the output scope and pricing. No padding, though the pricing clause is appended without a clear lead-in about sequencing.

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?

With no annotations, no output schema, and four undocumented parameters, the description should do more. It states what the tool returns at a high level but leaves the meaning of every input unexplained, which is the main gap an agent would hit when actually invoking it.

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

Parameters1/5

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

All four parameters (texte, langue, contexte, relu_par_humain) have 0% schema description coverage, and the description says nothing about any of them — not even that texte is the input under review or what langue/contexte control. The description does not compensate for the total gap in input documentation.

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?

States a specific verb and resource: an 'EU AI Act art. 50 transparency check' that determines whether AI disclosure is required, whether it is present, and supplies the disclosure text plus machine-readable metadata. The purpose is precise and clearly distinct from catalog/search/audit siblings, though it never names a sibling to contrast with.

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?

The description implies the compliance context (EU AI Act art. 50) but gives no explicit when-to-use guidance, no prerequisites, and no alternatives or exclusions. An agent has to infer the triggering situation entirely from the purpose sentence.

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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